US20050114505A1 - Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system - Google Patents

Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system Download PDF

Info

Publication number
US20050114505A1
US20050114505A1 US10/898,016 US89801604A US2005114505A1 US 20050114505 A1 US20050114505 A1 US 20050114505A1 US 89801604 A US89801604 A US 89801604A US 2005114505 A1 US2005114505 A1 US 2005114505A1
Authority
US
United States
Prior art keywords
log data
log
data
raw
analyzers
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US10/898,016
Inventor
Jason DeStefano
Tomasz Mojsa
Thomas Grabowski
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Cloud Software Group Inc
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to US10/898,016 priority Critical patent/US20050114505A1/en
Assigned to LOGLOGIC, INC. reassignment LOGLOGIC, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: DESTEFANO, JASON MICHAEL, GRABOWSKI, THOMAS HUNT SCHABO, MOJSA, TOMASZ MARIUSZ
Publication of US20050114505A1 publication Critical patent/US20050114505A1/en
Priority to US13/536,720 priority patent/US9298691B2/en
Assigned to TIBCO SOFTWARE INC. reassignment TIBCO SOFTWARE INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: LOGLOGIC, INC.
Assigned to CLOUD SOFTWARE GROUP, INC. reassignment CLOUD SOFTWARE GROUP, INC. CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: TIBCO SOFTWARE INC.
Abandoned legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/205—Parsing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/06—Generation of reports
    • H04L43/062—Generation of reports related to network traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0876—Network utilisation, e.g. volume of load or congestion level
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1416—Event detection, e.g. attack signature detection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
    • H04L41/5061—Network service management, e.g. ensuring proper service fulfilment according to agreements characterised by the interaction between service providers and their network customers, e.g. customer relationship management
    • H04L41/5074—Handling of user complaints or trouble tickets

Definitions

  • This invention relates to computer network monitoring. More particularly, it relates to handling the log data generated by such log-producing devices and processes as network firewalls, routers, file servers, VPN servers, operating systems, software applications and the like.
  • a computer firewall is one such device. At the simplest level, it may comprise hardware and/or software that filters the information coming through a network connection (most commonly an Internet connection) into a private network or computer system. If an incoming packet of information is flagged by the filters, it is not allowed to pass through the firewall.
  • a network connection most commonly an Internet connection
  • a firewall can implement security rules. For example, a network owner/operator might allow only one, certain computer on a LAN to receive public File Transfer Protocol (FTP) traffic. The FTP protocol is used to download and upload files. Accordingly, the firewall would allow FTP connections only to that one computer and prevent them on all others.
  • the administrator of a private network can set up rules such as this for FTP servers, Web servers, Telnet servers, and the like.
  • firewalls use one or more of the following methods to restrict the information coming in and out of a private network:
  • IP Internet Protocol
  • TCP Transport Control Protocol
  • HTTP Hypertext Transfer Protocol
  • FTP File Transfer Protocol
  • UDP User Datagram Protocol
  • ICMP Internet Control Message Protocol
  • SMTP Simple Mail Transport Protocol
  • SNMP Simple Network Management Protocol
  • a company might use a firewall or a router to enable one or two computers on its private network to handle a specific protocol and prohibit activity using that protocol on all of its other networked computers.
  • a firewall may be used to block access to certain ports and/or permit port [#] access only on a certain computer.
  • Firewalls can also be set to “sniff” each data packet for certain words or phrases. For example, a firewall could be set to exclude any packet containing the word “nude.” Alternatively, a firewall may be set up such that only certain types of information, such as e-mail, are allowed to pass through.
  • raw log data One particular type of raw log data is known as “syslog data.”
  • Log data from VPN servers, firewalls and routers commonly comprises date and time information along with the IP addresses of the source and destination of data packets and a text string indicating the action taken by the data log-producing device—e.g., “accept” or “deny” or “TCP connection dropped.”
  • An example of a raw log data from a Virtual Private Network (VPN) server is reproduced in Table I.
  • Log data from other sources comprises information relevant to the providing source.
  • An example of raw log data from an e-mail server (“sendmail” log data) is reproduced in Table II.
  • parsed and summarized data is often more useful and convenient for monitoring network performance, real-time network troubleshooting and the optimization of security parameters, regulatory compliance and/or company policy may necessitate the storage of raw log data.
  • the above-described systems stored parsed log data and only later forwarded the raw log data, the reliability of the full raw log data streams was reduced. Furthermore, delay issues complicated the raw log data storage and the growing volume of log data created logistical problems. The present invention solves these problems.
  • Raw log data is, in one exemplary embodiment, received by a raw log server, stored in complete form in a database and sent to a networked log data analyzer for parsing, summarizing and routine reporting.
  • the raw log data may be received using a first protocol from the log-producing network devices on the same local area network as the raw log server and from a log data analyzer at a remote location on a different network using a second protocol over a wide area network.
  • the remote log data analyzer may encrypt and/or compress the raw log data prior to periodically sending it over a WAN to the raw log server.
  • Database management may include processes which archive and/or purge the stored raw log data after a predefined time interval, in response to a predetermined event(s) and/or in response to data storage capacity constraints.
  • Queries and reports may be run on the database maintained by the raw log server to retrieve the raw log data. Queries and reports may also be run from a central management station to retrieve and merge reports form the various network log data analyzers.
  • FIG. 1 is a schematic representation of a local network comprising a raw log server and a plurality of log data analyzers and a remote network linked to the local network by a WAN.
  • FIG. 2A is a schematic diagram depicting the flow of raw log data according to one embodiment of the invention.
  • FIG. 2B is a schematic diagram depicting the flow of parsed and/or summarized log data in one representative embodiment of the invention.
  • FIGS. 3A through 3F are flowcharts of a data processing method according to certain embodiments of the invention.
  • FIG. 4 is a flowchart of a data processing method according to one embodiment of the invention for obtaining a report from a central management station.
  • Log data is commonly comprised of a text string.
  • An example of log data from a VPN server is shown in Table I and an example of log data from an e-mail server is shown in Table II.
  • Table I An example of log data from a VPN server is shown in Table I and an example of log data from an e-mail server is shown in Table II.
  • Dhcp Unicasting DHCPREQUEST xid eeee36bf to 10.0.0.1 ⁇ 2>Mar 25 00:17:39 10.0.0.98 ⁇ 134> 3181 03/25/2004 00:17:54 tEvtLgMgr 0 : Address Pool [11]
  • Dhcp address bound to 10.0.0.184-255.255.255.0 -- renewal in 21600 seconds.
  • Log-producing devices such as routers and firewalls may be in networked data communication with one or more raw log servers.
  • the log-producing devices may send the raw log data to the raw log server upon creation or may buffer the raw log data for burst transmission.
  • the raw log server may insert the text string comprising the raw log data into a database together with identifying and/or indexing information.
  • a process using a flat file arrangement may be used.
  • the text string may be stored together with the identity of the log-producing device and a date and time stamp.
  • the identity of the log-producing device may be its IP address or any other unique identifier.
  • the time stamp may be the local raw log server's network time, Coordinated Universal Time (UTC), or a combination of local time and the time zone of the log-producing device.
  • the text string comprising the raw log data may be encoded in any suitable text encoding scheme such as the American Standard Code for Information Interchange (ASCII).
  • ASCII American Standard Code for Information Interchange
  • the database may be any database or file capable of storing and retrieving data in the format sent by the log-producing devices.
  • a database is MySQL.
  • One example of a file is a flat file.
  • the data may be indexed and/or otherwise identified, but it is stored in the database either in the form received or in a form which has a one-to-one correlation with the form in which it was received so as to ensure the integrity of the data—i.e., the raw log data is stored, but not manipulated in any manner which could create any ambiguity in its content.
  • the raw log server may also forward the raw log data to a particular log data analyzer on the LAN.
  • the raw log server may include a table which correlates log-producing devices with one or more particular log data analyzers. By consulting the table, the raw log server may forward the raw log data to the appropriate log data analyzer(s).
  • the data may include the identity of the log-producing device, the identity of the raw log server, a time stamp, and/or any other information needed for proper routing and processing.
  • Raw log data from a log-producing device and raw log data being forwarded by the raw log server to log data analyzer may be sent using a first data transmission protocol.
  • this first protocol is UDP, a protocol which requires relatively little network overhead.
  • the UDP protocol is relatively weak from security and reliability standpoints and thus may be suitable in this context only for use on a local network.
  • FIG. 1 is a schematic representation of a system according to one embodiment of the invention.
  • a LAN 109 at a location 120 provides data communication between and among raw log server 110 , one or more log data analyzers 111 , 112 , and log-producing devices such as firewalls 113 & 116 and routers 114 & 115 .
  • Security management functions may be controlled from a management station 117 which, in some embodiments may be a personal computer or workstation.
  • LAN 109 may be in data communication with a WAN 107 via gateway 108 .
  • the present invention may also be used to collect and store log data generated by log-producing devices 101 , 102 at a remote location 100 —i.e., a location not directly connected to the private network or local area network (LAN) 109 .
  • a remote location 100 i.e., a location not directly connected to the private network or local area network (LAN) 109 .
  • WAN wide area network
  • Remote LAN 103 may be in data communication with WAN 107 via gateway 104 .
  • log-producing devices 101 & 102 are usually not equipped with means for encrypting and/or compressing data prior to transmission, it has been found to be advantageous to provide for those functions in a log data analyzer 105 to which the log-producing devices may directly communicate over remote LAN 103 .
  • log-producing devices such as firewall 101 and router 102 at a remote location 100 are in data communication (via a LAN 103 ) with a dedicated log data analyzer 105 .
  • the log data analyzer 105 may collect raw log data from the log-producing devices, encrypt and compress the raw log data and then periodically send it to the raw log server over the WAN 107 using a second protocol.
  • raw log data may be collected in one-minute intervals and sent using a burst mode of data transmission over the WAN in order to conserve network resources—burst mode generally being more efficient than piecemeal transmissions.
  • the TCP protocol is used because it provides a more robust environment for data transmission than UDP and thus provides greater confidence in the integrity of the log data stored by the raw log server.
  • the local log data analyzer 105 may collect a predetermined quantity of log data before sending it to the raw log server 110 or, alternatively, may send raw log data periodically—e.g., one minute's worth of raw log data may be collected by the local log data analyzer 105 and then sent to the raw log server 110 after encryption and compression. It is not necessary to the practice of the invention that the raw log data be encrypted or compressed prior to transmission.
  • Raw log data received by a raw log server 110 from a remote log data analyzer may be processed differently than the raw log data obtained from the local log-producing devices 113 , 114 , 115 , 116 . For one reason, this is because this raw log data need not be forwarded to a log data analyzer (such as 111 or 112 ) unless a redundancy in this function is, in which case the raw log data may be forwarded to one or more log data analyzers.
  • the remote log data analyzer 105 already has the raw log data and may proceed to parse, store and summarize the raw log data from its associated log-producing devices 101 , 102 .
  • Another reason is that it may be desirable to have the raw log data stored chronologically in the raw log database and the transmission of the raw log data over the WAN 107 is delayed.
  • the delay may be due to the fact that the remote raw log data is collected into one-minute intervals prior to transmission to the raw log server and/or delays in transmission over the WAN 107 .
  • Raw log data generated at remote location 100 by log-producing devices 101 & 102 is sent to remote log data analyzer 105 which forwards the raw log data for transmission over WAN 107 to raw log server 110 at physical location 120 remote from location 100 .
  • Log-producing devices 113 - 116 at location 120 send raw log data to raw log server 110 which stores the raw log data in physical, scalable internal and/or external storage and forwards the raw log data to a selected log data analyzer (e.g., 111 ) which may be associated with a certain log-producing device.
  • Examples of external scalable data storage include Storage Area Networks (SAN's) and Network Attached Storage (NAS).
  • FIG. 2B The flow of parsed and/or summarized log data according to one illustrative embodiment is shown schematically in FIG. 2B .
  • database reports comprised of parsed and/or summarized log data may be sent from log data analyzer 105 at remote location 100 to the security management station 117 via WAN 107 while a report from a database maintained by log data analyzer 111 is sent to management station 117 .
  • the data communications link between log data analyzer 111 and management station 117 may be a local area network.
  • one process is used to receive the live, raw log data streams using a first protocol from the local log-producing devices and another process gathers the compressed, encrypted data streams from remote locations sent using a second protocol and a third process merges the two data streams into a single, sequentially ordered database table.
  • This may be advantageously accomplished in a “batch mode” wherein the raw log data gathering is segmented into certain time intervals. When an interval closes, the data from both the local and remote log-data-producing devices may be forwarded to the merge process for insertion into the database in proper order.
  • the data reception processes can proceed independently and not require real-time synchronization or the insertion, as opposed to appending, of live data into an open database table.
  • FIGS. 3A, 3B , 3 C and 3 D are flowcharts depicting the steps in representative processes for collecting and storing raw log data according to the present invention. These processes may occur in parallel—i.e., substantially simultaneously—or they may be performed sequentially. The process depicted in FIG. 3A may take place at a location remote from those occurring in a local system, depicted in FIGS. 3B through 3F .
  • sets of raw log data from one or more log-producing devices are collected periodically in a certain time interval set by the period timer.
  • the process begins at block 302 with the initiation of a new set of raw log data, denominated “Period N”.
  • the interval timer is started at block 304 and, at block 306 , data is collected and stored in a buffer in a log data analyzer which is in direct data communication with the log-producing device(s).
  • decision diamond 308 the current value of the timer is read and compared to the selected interval. If the period has not yet expired, the process proceeds to decision diamond 311 where a determination is made of whether the buffer is full.
  • a new period, N+1 is created by incrementing the period counter (Block 310 ) and beginning a new set of raw log data (Block 302 ).
  • the data set for period N may be compressed at block 314 and written to a scratch file on a disk at block 316 .
  • the buffer holding the data set for period N may be cleared, thereby making it available for use with subsequent raw log data sets.
  • the raw log server may be at a location remote from the equipment performing the process of FIG. 3A and the data set may be sent to the raw log server over a WAN which may be a public network such as the Internet.
  • a concurrent process is shown for sending data sets to the raw log server.
  • the process examines data sets stored by the data collection process of FIG. 3A at block 316 to determine whether any scratch files are older than 60 seconds. If not, the process waits for one second (block 319 ) and then retests the age of the files (diamond 312 ).
  • the process opens a connection to the raw log server at block 313 and, at block 315 , sends the file (oldest file first) to the raw log server.
  • the file may be further compressed and/or encrypted prior to being sent.
  • the file may have a hash value, such as an MD5 hash, attached to further assist in integrity checking.
  • the connection to the raw log server is closed and the process resumes its search for data sets more than 60 seconds old (diamond 312 ).
  • FIGS. 3C and 3D an analogous process is shown for a system wherein the log-producing devices are in directdata communication with the raw log server—e.g., the log-producing devices are connected by a LAN to the raw log server.
  • the raw log data is collected in files corresponding to certain time periods.
  • Time periods are defined in the process of FIG. 3C wherein the period N begins at block 320 with the starting of a timer. In one preferred embodiment, the data is collected into one-minute time intervals. It is convenient, but not necessary to select the same period length for the process of FIG. 3C as that for the remote device(s) as shown in FIG. 3A .
  • the process sets a flag to inform the process of FIG. 3D that a new file should be created.
  • the process waits for the period to come to an end, at which point the process returns to block 320 and a new period begins.
  • log data is collected from local log-producing devices such as firewalls at block 322 .
  • the raw log data may also be forwarded to a particular log data analyzer(s) associated with the particular log-producing device whose data is being stored. This is done by a process that consults a table which correlates log-producing devices with log data analyzers. The table may be simple or may include complex filtering rules and resultant actions.
  • the process adds a header which may contain a time stamp and/or a device identifier to the raw message received at block 325 .
  • the flag which may be set by the timing process ( FIG.
  • Data sets collected by the process depicted in FIG. 3A at the remote location may be received and processed by the raw log server according to the process shown in FIG. 3E .
  • a set of raw log data for time period N is received at the raw log server following transmission over a data communications network(s). If the raw log data has been encrypted for transmission, the data may be restored to its original format by decrypting it at block 341 . If the data has been hashed, the data is hashed again and the hash values compared to test integrity in block 342 . If the raw log data has been compressed, it may be decompressed at block 344 . The order of blocks 341 , 342 and 344 may be altered in certain embodiments.
  • the hash check should be performed on the raw log data in the state in which the first hash was performed.
  • the hash check, data decompression and/or decryption may be performed elsewhere in the system prior to receipt by the raw log server.
  • the restored raw log data from the remote device may be stored in a temporary database file for the particular time period and particular device.
  • FIG. 3F illustrates the steps in a process that collects the data sets for a certain period M and stores the collected data set in a database which may be maintained by the raw log server.
  • concatenation is delayed for a period of T minutes to allow for some delay in the receipt of data sets from the remote location.
  • the process continuously scans the temporary database files produced by the processes depicted in FIGS. 3B and 3C to determine whether any of those files are more than T minutes old—i.e., whether the terminus of period M is more than T minutes prior to the current time. If such files are found, they are collected for the period M at block 352 and concatenated at block 354 .
  • the raw log data set so produced may then be sorted at block 356 .
  • the sort may be chronological—i.e., the raw log data for the local and remote log-producing devices may be placed into chronological order prior to storage in the raw log server's database for the period M (as shown at block 358 ).
  • the raw log server may be equipped with attached storage and/or a connection to Network Attached Storage, a storage area network (SAN) (which, in one preferred embodiment, is a Fibre Channel network), WORM (Write Once, Read Many) storage and other real-time data storage means.
  • SAN storage area network
  • WORM Write Once, Read Many
  • the use of external storage allows simple growth or expansion of the stored log data over time.
  • the raw log server may also be equipped with means for archival data storage such as magnetic tape or optical media.
  • the database management process may include provisions for periodically moving raw log data from storage in the database to archival storage. Alternatively, data may simply be deleted from the database at certain intervals, upon aging to a predetermined value, upon some other predefined event or upon command from the data management station.
  • parsed and/or summarized log data may be stored by the system in databases or files maintained by log data analyzers ( 105 , 111 , 112 ).
  • a firewall may produce upwards of 10 million various messages (i.e., log data) per day. This quantity of raw log data is frequently too much for a network administrator to analyze effectively. Accordingly, methods have been developed to parse and summarize log data.
  • the exemplary parser parses the received raw log data to extract fields based upon log data message type, and generates Structured Query Language (SQL) statements from the extracted fields. Subsequently, a database inserter inserts the SQL statements into database tables in memory, according to the message type, such as accept, deny or other.
  • a summarizer summarizes the SQL statements stored in the database tables over various intervals of time, and copies the summarized SQL statements to tables stored on disk. The summarizer determines which sets of SQL statements have identical source IP, destination IP, and destination port numbers, irrespective of the source port numbers of the SQL statements. The summarizer then creates a new statement (i.e., message) generated from the 50 messages, for example.
  • the summarizer may repeat the above summarization process over the SQL statements stored in the tables for other fields of commonality to create other new condensed statements.
  • the summarizer creates a fine-grained accept data chunk comprising a condensation of the SQL statements stored in the tables, based upon predefined fields of commonality (e.g., source IP, destination IP, and destination port numbers) and one or more fields of uniqueness (e.g., source port number).
  • Exemplary summarized tables may include fine-grained deny tables, 1-hour accept tables, 24-hour accept tables, and 24-hour deny tables.
  • the tables may be configured to store data over other periods of time (e.g., 10-minute accept tables to 30-day accept and deny tables).
  • the fine-grained deny table stores data for thirty days.
  • the system may include a security management station 117 that may, in certain embodiments, be implemented in software on a personal computer or workstation in data communication with the private network.
  • the management station may be implemented in dedicated hardware.
  • the management station may be used to retrieve data from the databases maintained by the raw log server(s) 110 and/or the log data analyzer(s) 105 , 111 , 112 .
  • the management station 117 may include one or more processes for distributing database queries to the appropriate log data analyzers and aggregating the responses received from individual log data analyzers (database reports) into a single report.
  • database reports database reports
  • the management station might query all of the networked log data analyzers for summarized data in that interval and then aggregate that data into a single report.
  • the management station might query only the log data analyzer associated with the particular firewall assigned to that port.
  • FIG. 4 One illustrative process for obtaining a report from a central management station is shown in flowchart form in FIG. 4 .
  • the process begins at block 402 with a user selecting a report from one or more log data analyzers.
  • the selection may be made of one particular log-producing device or all of the log-producing devices on the system.
  • the user may select multiple (but less than all) log-producing devices, as desired.
  • An example of a situation wherein a system administrator might desire a report from a single log-producing device is when a security attack on a the system was made through a particular port—e.g., a Telnet port—in which case parsed and/or summarized log data from the log-producing device associated with the system's Telnet port(s) would be sought.
  • a particular port e.g., a Telnet port—in which case parsed and/or summarized log data from the log-producing device associated with the system's Telnet port(s) would be sought.
  • the user may select the time period to be covered by the report.
  • the order of blocks 402 and 404 may be reversed in some embodiments or all of the selections may be made at one time on one query screen.
  • the process identifies the particular log data analyzer(s) whose databases need to be queried in order to compile the report requested by the user. In one preferred embodiment, this determination is accomplished by a table look up on the raw log server, but this information may be stored elsewhere, including the management station itself.
  • a database query (or queries in the case of multiple log data analyzers) is formulated and sent to the log data analyzer(s) hosting the database(s) of interest identified in block 406 . Each queried log data analyzer on the system will then respond by sending a database report of parsed and/or summarized log data corresponding to the time period selected. The reports are received by the management station at block 410 .
  • a log data analyzer may, in certain embodiments, store summarized log data in a database and respond to queries from a centralized management station.
  • One such process may include: receiving raw log data in a log data analyzer; parsing the raw log data; summarizing the parsed log data; storing the summarized data in a database maintained by the log data analyzer; receiving a database query from a management station; generating a database report in the log data analyzer from the summarized data in response to the query received from the management station; and, sending the database report to the management station.
  • the database report may include the time period of the summarized data and the data in the report may be sorted by the time period of the summarized data. At the option of the user, the data in the report may be limited by the time period of the summarized data.
  • log-producing devices in this description have been firewalls and routers, and the log data has related to networking operations, it is to be understood that other of the many log-producing devices, such as mail servers and the like, and other log data, such as operation status, errors and other events, could be used according to the present invention.

Abstract

A system and method is disclosed for collecting, storing and reporting raw log data from log-producing devices such as firewalls and routers. The log-producing devices may be both local and remote—i.e., linked to a raw log server via a LAN and/or a WAN. A log data analyzer at a remote location gathers log data from devices at that remote location into time-defined sets and then sends those sets over a WAN (which may be the Internet) to a raw log server using a first protocol. Local log-producing devices may send their log data to the log data analyzer via a LAN using a second protocol. The log data analyzer forwards the raw log data local devices to an appropriate log data analyzer for parsing, summarizing and storage in one or more databases. The raw log server combines local and remote sets of raw log data for a given time period and stores them in a storage area of raw log data. A central management station is used to query the various databases in the system and to merge database reports into a single report for display.

Description

    CROSS-REFERENCES TO RELATED APPLICATIONS
  • This case is related to: U.S. Patent Application No. 60/525,401, filed Nov. 26, 2003 and entitled “System and Method for Summarizing Log Data;” U.S. Patent Application No. 60/525,465, filed Nov. 26, 2003 and entitled “System and Method for Parsing Log Data;” United States patent application entitled “System and Method for Storing Raw Log Data” filed of even date herewith; United States patent application entitled “System and Method for the Collection and Transmission of Log Data over a Wide Area Network” filed of even date herewith; United States patent application entitled “Method for Processing Log Data from Local and Remote Log-producing Devices” filed of even date herewith; United States patent application entitled “Method and Apparatus for Storing and Reporting Summarized Log Data” filed of even date herewith.
    • BACKGROUND OF THE INVENTION
  • 1. Field of the Invention
  • This invention relates to computer network monitoring. More particularly, it relates to handling the log data generated by such log-producing devices and processes as network firewalls, routers, file servers, VPN servers, operating systems, software applications and the like.
  • 2. Description of the Related Art
  • Computer networks in general, and private networks such as Local Area Networks (LANs) and intranets in particular, require security devices and processes to protect them from unauthorized access and/or manipulation. A computer firewall is one such device. At the simplest level, it may comprise hardware and/or software that filters the information coming through a network connection (most commonly an Internet connection) into a private network or computer system. If an incoming packet of information is flagged by the filters, it is not allowed to pass through the firewall.
  • A firewall can implement security rules. For example, a network owner/operator might allow only one, certain computer on a LAN to receive public File Transfer Protocol (FTP) traffic. The FTP protocol is used to download and upload files. Accordingly, the firewall would allow FTP connections only to that one computer and prevent them on all others. The administrator of a private network can set up rules such as this for FTP servers, Web servers, Telnet servers, and the like.
  • Typically, firewalls use one or more of the following methods to restrict the information coming in and out of a private network:
      • packet filtering—data packets that meet the criteria set of the filter are allowed to proceed to the requesting system while those that do not are blocked from further transmission.
      • proxy service—information from an external network (such as the Internet) is retrieved by the firewall and subsequently sent to the requesting system. The effect of this action is that the remote computer on the external network does not establish direct communication with a computer on the private network other than the proxy server.
      • stateful inspection—a comparison of certain key parts of data packets to a database of trusted information. Data going from the private network to the public network is monitored for specific defining characteristics and incoming information is compared to those characteristics. If the comparison is a match within defined parameters, the data is allowed-to pass through the firewall.
  • A company might also use a firewall to block all access to certain IP addresses or allow access only to specific domain names. Protocols define how a client and server will exchange information. Common protocols include: Internet Protocol (IP), the main protocol of the Internet; Transport Control Protocol (TCP), used to disassemble and assemble information that travels over the Internet; Hypertext Transfer Protocol (HTTP), used for Web pages; File Transfer Protocol (FTP), used to download and upload computer files; User Datagram Protocol (UDP), used for information that does not require a response such as streaming audio and video; Internet Control Message Protocol (ICMP), used by a router to exchange information with another router; Simple Mail Transport Protocol (SMTP), used to send text e-mail; Simple Network Management Protocol (SNMP), used to obtain system information from a remote computer; and, Telnet, which is used to execute commands on a remote computer.
  • A company might use a firewall or a router to enable one or two computers on its private network to handle a specific protocol and prohibit activity using that protocol on all of its other networked computers.
  • Similarly, a firewall may be used to block access to certain ports and/or permit port [#] access only on a certain computer.
  • Firewalls can also be set to “sniff” each data packet for certain words or phrases. For example, a firewall could be set to exclude any packet containing the word “nude.” Alternatively, a firewall may be set up such that only certain types of information, such as e-mail, are allowed to pass through.
  • Many IT devices and processes produce a log of their activities (hereinafter “raw log data”). One particular type of raw log data is known as “syslog data.” Log data from VPN servers, firewalls and routers commonly comprises date and time information along with the IP addresses of the source and destination of data packets and a text string indicating the action taken by the data log-producing device—e.g., “accept” or “deny” or “TCP connection dropped.” An example of a raw log data from a Virtual Private Network (VPN) server is reproduced in Table I. Log data from other sources comprises information relevant to the providing source. An example of raw log data from an e-mail server (“sendmail” log data) is reproduced in Table II.
  • It will be appreciated that periods of high network activity generate large quantities of log data. During an attempted security breach, it may be necessary for network administrators to access the log data to determine the nature of the attack and/or adjust the security parameters in order to better defend against the attack. Although systems may provide a means for viewing the log data in real time or near real time, the sheer quantity of data generated makes it largely impractical to manually glean useful information from raw log data. Accordingly, systems and methods have been developed for parsing and summarizing log data in databases upon which queries may be run in near real time to retrieve relevant information.
  • A system and method for parsing log data is disclosed in commonly-owned U.S. provisional patent application Ser. No. 60/525,465 filed Nov. 26, 2003, and a system and method for summarizing log data is disclosed in commonly-owned U.S. provisional patent application Ser. No. 60/525,401 filed Nov. 26, 2003, both of which are hereby incorporated by reference.
  • Although parsed and summarized data is often more useful and convenient for monitoring network performance, real-time network troubleshooting and the optimization of security parameters, regulatory compliance and/or company policy may necessitate the storage of raw log data. Inasmuch as the above-described systems stored parsed log data and only later forwarded the raw log data, the reliability of the full raw log data streams was reduced. Furthermore, delay issues complicated the raw log data storage and the growing volume of log data created logistical problems. The present invention solves these problems.
    • SUMMARY OF THE INVENTION
  • Raw log data is, in one exemplary embodiment, received by a raw log server, stored in complete form in a database and sent to a networked log data analyzer for parsing, summarizing and routine reporting. The raw log data may be received using a first protocol from the log-producing network devices on the same local area network as the raw log server and from a log data analyzer at a remote location on a different network using a second protocol over a wide area network. The remote log data analyzer may encrypt and/or compress the raw log data prior to periodically sending it over a WAN to the raw log server. Database management may include processes which archive and/or purge the stored raw log data after a predefined time interval, in response to a predetermined event(s) and/or in response to data storage capacity constraints. Further database management handles the process of integrating the local raw log data in the first protocol and the remote raw log data in the second protocol. Queries and reports may be run on the database maintained by the raw log server to retrieve the raw log data. Queries and reports may also be run from a central management station to retrieve and merge reports form the various network log data analyzers.
    • BRIEF DESCRIPTION OF THE DRAWING FIGURES
  • FIG. 1 is a schematic representation of a local network comprising a raw log server and a plurality of log data analyzers and a remote network linked to the local network by a WAN.
  • FIG. 2A is a schematic diagram depicting the flow of raw log data according to one embodiment of the invention.
  • FIG. 2B is a schematic diagram depicting the flow of parsed and/or summarized log data in one representative embodiment of the invention.
  • FIGS. 3A through 3F are flowcharts of a data processing method according to certain embodiments of the invention.
  • FIG. 4 is a flowchart of a data processing method according to one embodiment of the invention for obtaining a report from a central management station.
    • DETAILED DESCRIPTION
  • Log data is commonly comprised of a text string. An example of log data from a VPN server is shown in Table I and an example of log data from an e-mail server is shown in Table II.
    TABLE I
    <2>Mar 25 00:17:38 10.0.0.98 <134> 3181 03/25/2004 00:17:54 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee36bf to 10.0.0.1
    <2>Mar 25 00:17:39 10.0.0.98 <134> 3181 03/25/2004 00:17:54 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.184-255.255.255.0 -- renewal
    in 21600 seconds.
    <2>Mar 25 00:17:39 10.0.0.98 <134> 3181 03/25/2004 00:18:02 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee684c to 10.0.0.1
    <2>Mar 25 00:17:39 10.0.0.98 <134> 3181 03/25/2004 00:18:02 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.185-255.255.255.0 -- renewal
    in 21600 seconds.
    <2>Mar 25 00:17:55 10.0.0.98 <134> 3181 03/25/2004 00:18:10 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee1705 to 10.0.0.1
    <2>Mar 25 00:17:56 10.0.0.98 <134> 3181 03/25/2004 00:18:10 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.183-255.255.255.0 -- renewal
    in 21600 seconds.
    <2>Mar 25 01:09:02 10.0.0.98 <134> 3181 03/25/2004 01:09:21 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee2683 to 10.0.0.1
    <2>Mar 25 01:09:03 10.0.0.98 <134> 3181 03/25/2004 01:09:21 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.102-255.255.255.0 -- renewal
    in 21600 seconds.
    <2>Mar 25 02:44:53 10.0.0.98 <134> 3181 03/25/2004 02:45:12 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee19fa to 10.0.0.1
    <2>Mar 25 02:44:53 10.0.0.98 <134> 3181 03/25/2004 02:45:13 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.199-255.255.255.0 -- renewal
    in 21600 seconds.
    <2>Mar 25 06:17:41 10.0.0.98 <134> 3181 03/25/2004 06:17:54 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee36bf to 10.0.0.1
    <2>Mar 25 06:17:41 10.0.0.98 <134> 3181 03/25/2004 06:17:54 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.184-255.255.255.0 -- renewal
    in 21600 seconds.
    <2>Mar 25 06:17:41 10.0.0.98 <134> 3181 03/25/2004 06:18:02 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee684c to 10.0.0.1
    <2>Mar 25 06:17:41 10.0.0.98 <134> 3181 03/25/2004 06:18:02 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.185-255.255.255.0 -- renewal
    in 21600 seconds.
    <2>Mar 25 06:17:57 10.0.0.98 <134> 3181 03/25/2004 06:18:10 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee1705 to 10.0.0.1
    <2>Mar 25 06:17:57 10.0.0.98 <134> 3181 03/25/2004 06:18:10 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.183-255.255.255.0 -- renewal
    in 21600 seconds.
    <2>Mar 25 07:09:04 10.0.0.98 <134> 3181 03/25/2004 07:09:21 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee2683 to 10.0.0.1
    <2>Mar 25 07:09:04 10.0.0.98 <134> 3181 03/25/2004 07:09:21 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.102-255.255.255.0 -- renewal
    in 21600 seconds.
    <2>Mar 25 08:44:54 10.0.0.98 <134> 3181 03/25/2004 08:45:13 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: Unicasting DHCPREQUEST xid eeee19fa to 10.0.0.1
    <2>Mar 25 08:44:55 10.0.0.98 <134> 3181 03/25/2004 08:45:13 tEvtLgMgr 0 :
    Address Pool [11] Dhcp: address bound to 10.0.0.199-255.255.255.0 -- renewal
    in 21600 seconds.
  • TABLE II
    May 2 04:03:43 en1 sendmail[3893]: i4293bg03869:
    to=<sias@bookpeddlers.com>,<sweeper@bookpeddlers.com>, delay=00:00:06,
    xdelay=00:00:03, mailer=virthostmail, pri=74907, relay=bookpeddlers.com,
    dsn=2.0.0, stat=Sent (i4293eb03897 Message accepted for delivery)
    May 2 04:03:43 en1 sendmail[876]: i4201rO04491: to=<vkyvkofb@amnaes3.com>,
    delay=09:01:50, xdelay=00:00:00, mailer=esmtp, pri=120880,
    relay=218.106.116.147. [218.106.116.147], dsn=4.0.0, stat=Deferred:
    Connection refused by 218.106.116.147.
    May 2 04:03:44 en1 sendmail[3914]: i4293eb03897: to=vickilee@aol.com,
    delay=00:00:03, xdelay=00:00:00, mailer=esmtp, pri=44213, relay=mailin-
    03.mx.aol.com. [64.12.138.120], dsn=2.0.0, stat=Sent (OK)
    May 2 04:03:49 en1 sendmail[876]: i421IDo08289: to=<715tuoddme@ewmd41.com>,
    delay=07:45:35, xdelay=00:00:00, mailer=esmtp, pri=120882,
    relay=218.106.116.147., dsn=4.0.0, stat=Deferred: Connection refused by
    218.106.116.147.
    May 2 04:03:51 en1 sendmail[876]: i425I2h22324: to=<jlx7ivh@aswphamre.com>,
    delay=03:45:49, xdelay=00:00:00, mailer=esmtp, pri=120882,
    relay=218.106.116.147., dsn=4.0.0, stat=Deferred: Connection refused by
    218.106.116.147.
    May 2 04:03:52 en1 sendmail[876]: i424UG719748: to=<kq395gy@mnftphamrd.com>,
    delay=04:33:36, xdelay=00:00:00, mailer=esmtp, pri=120885,
    relay=218.106.116.147., dsn=4.0.0, stat=Deferred: Connection refused by
    218.106.116.147.
    May 2 04:03:52 en1 sendmail[876]: i421Qhb08867: to=<ysijamz@cnfdb3.com>,
    delay=07:37:09, xdelay=00:00:00, mailer=esmtp, pri=120886,
    relay=218.106.116.147., dsn=4.0.0, stat=Deferred: Connection refused by
    218.106.116.147.
    May 2 04:03:53 en1 sendmail[876]: i421Zhu09425: to=vickilee@aol.com,
    delay=07:28:10, xdelay=00:00:00, mailer=esmtp, pri=120886, relay=mailin-
    01.mx.aol.com., dsn=4.0.0, stat=Deferred: Connection reset by mailin-
    01.mx.aol.com.
    May 2 04:03:53 en1 sendmail[876]: i421Zhu09425: i4290jb00876: sender notify:
    Warning: could not send message for past 4 hours
    May 2 04:03:53 en1 sendmail[30594]: i3TAde725551: to=<crmvmrbmpjx@Xoom.de>,
    delay=2+22:24:13, xdelay=00:01:00, mailer=esmtp, pri=4817444, relay=xoom.de.
    [206.132.179.24], dsn=4.0.0, stat=Deferred: Connection timed out with
    xoom.de.
    May 2 04:03:53 en1 sendmail[30594]: i3TAER722740: to=<dc529a@mreds4.com>,
    delay=2+22:49:26, xdelay=00:00:00, mailer=esmtp, pri=4895345,
    relay=218.106.116.147., dsn=4.0.0, stat=Deferred: Connection refused by
    218.106.116.147.
    May 2 04:03:54 en1 sendmail[876]: i4290jb00876: to=<yynkrfc@mpoweredpc.net>,
    delay=00:00:01, xdelay=00:00:00, mailer=esmtp, pri=30986,
    relay=smtp17.bellnexxia.net. [206.47.199.31], dsn=5.1.1, stat=User unknown
    May 2 04:03:55 en1 sendmail[876]: i4290jb00876: i4290jc00876: return to
    sender: User unknown
    May 2 04:03:56 en1 sendmail[30594]: i3T7m0604310: to=<t_richter_au@tvr.ro>,
    delay=3+01:15:56, xdelay=00:00:02, mailer=esmtp, pri=4981040,
    relay=jera.tvr.ro. [212.54.100.7], dsn=4.2.0, stat=Deferred: 450
    <t_richter_au@tvr.ro>: User unknown in local recipient table
    May 2 04:03:56 en1 sendmail[876]: i4290jc00876: to=vickilee@aol.com,
    delay=00:00:01, xdelay=00:00:00, mailer=esmtp, pri=31086, relay=mailin-
    04.mx.aol.com., dsn=4.0.0, stat=Deferred: Connection reset by mailin-
    04.mx.aol.com.
    May 2 04:03:57 en1 sendmail[876]: i427SKB29427: to=vickilee@aol.com,
    delay=01:35:37, xdelay=00:00:00, mailer=esmtp, pri=120886, relay=mailin-
    04.mx.aol.com., dsn=4.0.0, stat=Deferred: Connection reset by mailin-
    04.mx.aol.com.
    May 2 04:03:57 en1 sendmail[30594]: i3T96f614079:
    to=<kapbfgeid1rkfw@monnsid.com>, delay=2+23:57:16, xdelay=00:00:00,
    mailer=esmtp, pri=4982464, relay=218.106.116.147., dsn=4.0.0, stat=Deferred:
    Connection refused by 218.106.116.147.
    May 2 04:03:57 en1 sendmail[876]: i423nw118194: to=<t45nxi@phanexe.com>,
    delay=05:13:59, xdelay=00:00:00, mailer=esmtp, pri=120888,
    relay=218.106.116.147., dsn=4.0.0, stat=Deferred: Connection refused by
    218.106.116.147.
    May 2 04:03:58 en1 sendmail[30594]: i3T8Oq708114:
    to=<wapw0j@ermephamre.com>, delay=3+00:39:06, xdelay=00:00:00, mailer=esmtp,
    pri=4985257, relay=218.106.116.147., dsn=4.0.0, stat=Deferred: Connection
    refused by 218.106.116.147.
    May 2 04:03:59 en1 sendmail[30594]: i3T8CR706211: to=<fq402cyf@mreds4.com>,
    delay=3+00:51:32, xdelay=00:00:00, mailer=esmtp, pri=4985291,
    relay=218.106.116.147., dsn=4.0.0, stat=Deferred: Connection refused by
    218.106.116.147.
  • Log-producing devices such as routers and firewalls may be in networked data communication with one or more raw log servers. The log-producing devices may send the raw log data to the raw log server upon creation or may buffer the raw log data for burst transmission.
  • Upon receipt of the raw log data, the raw log server may insert the text string comprising the raw log data into a database together with identifying and/or indexing information. Alternatively, a process using a flat file arrangement may be used. For example, the text string may be stored together with the identity of the log-producing device and a date and time stamp. The identity of the log-producing device may be its IP address or any other unique identifier. The time stamp may be the local raw log server's network time, Coordinated Universal Time (UTC), or a combination of local time and the time zone of the log-producing device. The text string comprising the raw log data may be encoded in any suitable text encoding scheme such as the American Standard Code for Information Interchange (ASCII). The database may be any database or file capable of storing and retrieving data in the format sent by the log-producing devices. One example of a database is MySQL. One example of a file is a flat file. The data may be indexed and/or otherwise identified, but it is stored in the database either in the form received or in a form which has a one-to-one correlation with the form in which it was received so as to ensure the integrity of the data—i.e., the raw log data is stored, but not manipulated in any manner which could create any ambiguity in its content.
  • If the log data was received directly from a local log-producing device (e.g., a firewall or router on the same LAN as the raw log server), the raw log server may also forward the raw log data to a particular log data analyzer on the LAN. The raw log server may include a table which correlates log-producing devices with one or more particular log data analyzers. By consulting the table, the raw log server may forward the raw log data to the appropriate log data analyzer(s). The data may include the identity of the log-producing device, the identity of the raw log server, a time stamp, and/or any other information needed for proper routing and processing.
  • Raw log data from a log-producing device and raw log data being forwarded by the raw log server to log data analyzer may be sent using a first data transmission protocol. In one preferred embodiment, this first protocol is UDP, a protocol which requires relatively little network overhead. However, the UDP protocol is relatively weak from security and reliability standpoints and thus may be suitable in this context only for use on a local network.
  • FIG. 1 is a schematic representation of a system according to one embodiment of the invention. A LAN 109 at a location 120 provides data communication between and among raw log server 110, one or more log data analyzers 111, 112, and log-producing devices such as firewalls 113 & 116 and routers 114 & 115. Security management functions may be controlled from a management station 117 which, in some embodiments may be a personal computer or workstation. LAN 109 may be in data communication with a WAN 107 via gateway 108.
  • As illustrated in FIG. 1, the present invention may also be used to collect and store log data generated by log-producing devices 101, 102 at a remote location 100—i.e., a location not directly connected to the private network or local area network (LAN) 109. In such a situation, it is desirable to collect the raw log data using a log data analyzer 105 on the remote network and periodically forward the raw log data to the raw log server over a wide area network (WAN) 107 or the Internet. Remote LAN 103 may be in data communication with WAN 107 via gateway 104. Since the log-producing devices 101 & 102 are usually not equipped with means for encrypting and/or compressing data prior to transmission, it has been found to be advantageous to provide for those functions in a log data analyzer 105 to which the log-producing devices may directly communicate over remote LAN 103.
  • Thus, as illustrated in FIG. 1, log-producing devices such as firewall 101 and router 102 at a remote location 100 are in data communication (via a LAN 103) with a dedicated log data analyzer 105. The log data analyzer 105 may collect raw log data from the log-producing devices, encrypt and compress the raw log data and then periodically send it to the raw log server over the WAN 107 using a second protocol. For example, raw log data may be collected in one-minute intervals and sent using a burst mode of data transmission over the WAN in order to conserve network resources—burst mode generally being more efficient than piecemeal transmissions. In one preferred embodiment, the TCP protocol is used because it provides a more robust environment for data transmission than UDP and thus provides greater confidence in the integrity of the log data stored by the raw log server. The local log data analyzer 105 may collect a predetermined quantity of log data before sending it to the raw log server 110 or, alternatively, may send raw log data periodically—e.g., one minute's worth of raw log data may be collected by the local log data analyzer 105 and then sent to the raw log server 110 after encryption and compression. It is not necessary to the practice of the invention that the raw log data be encrypted or compressed prior to transmission.
  • Raw log data received by a raw log server 110 from a remote log data analyzer may be processed differently than the raw log data obtained from the local log-producing devices 113, 114, 115, 116. For one reason, this is because this raw log data need not be forwarded to a log data analyzer (such as 111 or 112) unless a redundancy in this function is, in which case the raw log data may be forwarded to one or more log data analyzers. The remote log data analyzer 105 already has the raw log data and may proceed to parse, store and summarize the raw log data from its associated log-producing devices 101, 102. Another reason is that it may be desirable to have the raw log data stored chronologically in the raw log database and the transmission of the raw log data over the WAN 107 is delayed. The delay may be due to the fact that the remote raw log data is collected into one-minute intervals prior to transmission to the raw log server and/or delays in transmission over the WAN 107.
  • The flow of raw log data according to one illustrative embodiment is shown schematically in FIG. 2A. Raw log data generated at remote location 100 by log-producing devices 101 & 102 is sent to remote log data analyzer 105 which forwards the raw log data for transmission over WAN 107 to raw log server 110 at physical location 120 remote from location 100. Log-producing devices 113-116 at location 120 send raw log data to raw log server 110 which stores the raw log data in physical, scalable internal and/or external storage and forwards the raw log data to a selected log data analyzer (e.g., 111) which may be associated with a certain log-producing device. Examples of external scalable data storage include Storage Area Networks (SAN's) and Network Attached Storage (NAS).
  • The flow of parsed and/or summarized log data according to one illustrative embodiment is shown schematically in FIG. 2B. In response to a query from management station 117, database reports comprised of parsed and/or summarized log data may be sent from log data analyzer 105 at remote location 100 to the security management station 117 via WAN 107 while a report from a database maintained by log data analyzer 111 is sent to management station 117. As shown in FIG. 1, the data communications link between log data analyzer 111 and management station 117 may be a local area network.
  • Inasmuch as merging live and compressed data streams into a single open database table may be problematic, in certain embodiments of the invention, one process is used to receive the live, raw log data streams using a first protocol from the local log-producing devices and another process gathers the compressed, encrypted data streams from remote locations sent using a second protocol and a third process merges the two data streams into a single, sequentially ordered database table. This may be advantageously accomplished in a “batch mode” wherein the raw log data gathering is segmented into certain time intervals. When an interval closes, the data from both the local and remote log-data-producing devices may be forwarded to the merge process for insertion into the database in proper order. In this way, the data reception processes can proceed independently and not require real-time synchronization or the insertion, as opposed to appending, of live data into an open database table. In other embodiments, it may be desired to keep the local and remote data streams separate (at the expense of reporting ease) in order to provide greater data integrity.
  • FIGS. 3A, 3B, 3C and 3D are flowcharts depicting the steps in representative processes for collecting and storing raw log data according to the present invention. These processes may occur in parallel—i.e., substantially simultaneously—or they may be performed sequentially. The process depicted in FIG. 3A may take place at a location remote from those occurring in a local system, depicted in FIGS. 3B through 3F.
  • In the process of FIG. 3A, sets of raw log data from one or more log-producing devices are collected periodically in a certain time interval set by the period timer. The process begins at block 302 with the initiation of a new set of raw log data, denominated “Period N”. The interval timer is started at block 304 and, at block 306, data is collected and stored in a buffer in a log data analyzer which is in direct data communication with the log-producing device(s). At decision diamond 308, the current value of the timer is read and compared to the selected interval. If the period has not yet expired, the process proceeds to decision diamond 311 where a determination is made of whether the buffer is full. If not, the process loops back to block 306 and the collection of raw log data continues. If, however, the period has expired or the buffer has become full, a new period, N+1, is created by incrementing the period counter (Block 310) and beginning a new set of raw log data (Block 302). Concurrently, the data set for period N may be compressed at block 314 and written to a scratch file on a disk at block 316. At block 318, the buffer holding the data set for period N may be cleared, thereby making it available for use with subsequent raw log data sets.
  • The raw log server may be at a location remote from the equipment performing the process of FIG. 3A and the data set may be sent to the raw log server over a WAN which may be a public network such as the Internet. In FIG. 3B, a concurrent process is shown for sending data sets to the raw log server. At decision diamond 312, the process examines data sets stored by the data collection process of FIG. 3A at block 316 to determine whether any scratch files are older than 60 seconds. If not, the process waits for one second (block 319) and then retests the age of the files (diamond 312). If one or more files older than 60 seconds are discovered (YES branch of diamond 312), the process opens a connection to the raw log server at block 313 and, at block 315, sends the file (oldest file first) to the raw log server. In certain embodiments, the file may be further compressed and/or encrypted prior to being sent. In addition, the file may have a hash value, such as an MD5 hash, attached to further assist in integrity checking. At block 317, the connection to the raw log server is closed and the process resumes its search for data sets more than 60 seconds old (diamond 312).
  • In FIGS. 3C and 3D, an analogous process is shown for a system wherein the log-producing devices are in directdata communication with the raw log server—e.g., the log-producing devices are connected by a LAN to the raw log server. In the particular embodiment illustrated, the raw log data is collected in files corresponding to certain time periods.
  • The process of FIG. 3C occurs substantially simultaneously with that illustrated in FIG. 3D. Time periods are defined in the process of FIG. 3C wherein the period N begins at block 320 with the starting of a timer. In one preferred embodiment, the data is collected into one-minute time intervals. It is convenient, but not necessary to select the same period length for the process of FIG. 3C as that for the remote device(s) as shown in FIG. 3A. At block 321, the process sets a flag to inform the process of FIG. 3D that a new file should be created. At diamond 326 and block 327 the process waits for the period to come to an end, at which point the process returns to block 320 and a new period begins.
  • Referring now to FIG. 3D, log data is collected from local log-producing devices such as firewalls at block 322. At block 324, the raw log data may also be forwarded to a particular log data analyzer(s) associated with the particular log-producing device whose data is being stored. This is done by a process that consults a table which correlates log-producing devices with log data analyzers. The table may be simple or may include complex filtering rules and resultant actions. The process adds a header which may contain a time stamp and/or a device identifier to the raw message received at block 325. At diamond 323 the flag which may be set by the timing process (FIG. 3C) is tested and, if not set, the process proceeds to block 328 where the data in the data buffer (which in certain embodiments may be in the RAM of a processor-based system) is written to a local file for period N. If the flag is found to be set (at diamond 323), a new file is opened, the old file is closed (block 329) and the writing of data to a new local file occurs at block 328.
  • Data sets collected by the process depicted in FIG. 3A at the remote location may be received and processed by the raw log server according to the process shown in FIG. 3E. At block 340, a set of raw log data for time period N is received at the raw log server following transmission over a data communications network(s). If the raw log data has been encrypted for transmission, the data may be restored to its original format by decrypting it at block 341. If the data has been hashed, the data is hashed again and the hash values compared to test integrity in block 342. If the raw log data has been compressed, it may be decompressed at block 344. The order of blocks 341, 342 and 344 may be altered in certain embodiments. In general, the hash check should be performed on the raw log data in the state in which the first hash was performed. Alternatively, the hash check, data decompression and/or decryption may be performed elsewhere in the system prior to receipt by the raw log server. At block 346, the restored raw log data from the remote device may be stored in a temporary database file for the particular time period and particular device.
  • FIG. 3F illustrates the steps in a process that collects the data sets for a certain period M and stores the collected data set in a database which may be maintained by the raw log server. In the process shown, concatenation is delayed for a period of T minutes to allow for some delay in the receipt of data sets from the remote location. In one particularly preferred embodiment, a three-minute period is selected (T=3 min.).
  • At block 350, the process continuously scans the temporary database files produced by the processes depicted in FIGS. 3B and 3C to determine whether any of those files are more than T minutes old—i.e., whether the terminus of period M is more than T minutes prior to the current time. If such files are found, they are collected for the period M at block 352 and concatenated at block 354. The raw log data set so produced may then be sorted at block 356. The sort may be chronological—i.e., the raw log data for the local and remote log-producing devices may be placed into chronological order prior to storage in the raw log server's database for the period M (as shown at block 358). It has been found that-system resources may be conserved and system performance improved if the raw log data sets are sorted prior to insertion into the database. It should also be understood that this process may also occur multiple times for period M if, for example, log data for period M from remote log data analyzers arrived at the raw log server at differing times where at least one set is more than T minutes old.
  • It will be appreciated that the order of blocks 316, 328 and 340 shown in the processes of FIGS. 3A, 3B and 3C is not predefined. The timing of the receipt of data sets from the remote process of FIG. 3A is not determinate—data transmission over the WAN may be delayed, perhaps for a significant length of time. However, the process of the present invention accommodates such timing uncertainties by performing batch-wise insertions of log data into the raw log data database. In this way, the database need be opened only for the insertion of sets of concatenated and sorted raw log data and the problems associated with adding randomly-received data to a database are avoided.
  • As noted above, the quantity of raw log data generated by log-producing devices on a network may be significant. Accordingly, the raw log server may be equipped with attached storage and/or a connection to Network Attached Storage, a storage area network (SAN) (which, in one preferred embodiment, is a Fibre Channel network), WORM (Write Once, Read Many) storage and other real-time data storage means. The use of external storage allows simple growth or expansion of the stored log data over time. The raw log server may also be equipped with means for archival data storage such as magnetic tape or optical media. The database management process may include provisions for periodically moving raw log data from storage in the database to archival storage. Alternatively, data may simply be deleted from the database at certain intervals, upon aging to a predetermined value, upon some other predefined event or upon command from the data management station.
  • As noted previously, parsed and/or summarized log data may be stored by the system in databases or files maintained by log data analyzers (105, 111, 112). A firewall may produce upwards of 10 million various messages (i.e., log data) per day. This quantity of raw log data is frequently too much for a network administrator to analyze effectively. Accordingly, methods have been developed to parse and summarize log data.
  • The exemplary parser parses the received raw log data to extract fields based upon log data message type, and generates Structured Query Language (SQL) statements from the extracted fields. Subsequently, a database inserter inserts the SQL statements into database tables in memory, according to the message type, such as accept, deny or other. A summarizer summarizes the SQL statements stored in the database tables over various intervals of time, and copies the summarized SQL statements to tables stored on disk. The summarizer determines which sets of SQL statements have identical source IP, destination IP, and destination port numbers, irrespective of the source port numbers of the SQL statements. The summarizer then creates a new statement (i.e., message) generated from the 50 messages, for example. The summarizer may repeat the above summarization process over the SQL statements stored in the tables for other fields of commonality to create other new condensed statements. Thus, in one embodiment of the invention, the summarizer creates a fine-grained accept data chunk comprising a condensation of the SQL statements stored in the tables, based upon predefined fields of commonality (e.g., source IP, destination IP, and destination port numbers) and one or more fields of uniqueness (e.g., source port number).
  • Exemplary summarized tables may include fine-grained deny tables, 1-hour accept tables, 24-hour accept tables, and 24-hour deny tables. In alternative embodiments of the invention, the tables may be configured to store data over other periods of time (e.g., 10-minute accept tables to 30-day accept and deny tables). In one embodiment of the invention, the fine-grained deny table stores data for thirty days.
  • As shown in FIG. 1, the system may include a security management station 117 that may, in certain embodiments, be implemented in software on a personal computer or workstation in data communication with the private network. Alternatively, the management station may be implemented in dedicated hardware.
  • The management station may be used to retrieve data from the databases maintained by the raw log server(s) 110 and/or the log data analyzer(s) 105, 111, 112. The management station 117 may include one or more processes for distributing database queries to the appropriate log data analyzers and aggregating the responses received from individual log data analyzers (database reports) into a single report. By way of example, if the system administrator wished to view a report covering all system traffic during a certain time interval, the management station might query all of the networked log data analyzers for summarized data in that interval and then aggregate that data into a single report. However, if the system administrator wished to view a summarized log data report for a certain network port, the management station might query only the log data analyzer associated with the particular firewall assigned to that port.
  • One illustrative process for obtaining a report from a central management station is shown in flowchart form in FIG. 4. The process begins at block 402 with a user selecting a report from one or more log data analyzers. In one embodiment of the invention, the selection may be made of one particular log-producing device or all of the log-producing devices on the system. In other embodiments, the user may select multiple (but less than all) log-producing devices, as desired. An example of a situation wherein a system administrator might desire a report from a single log-producing device is when a security attack on a the system was made through a particular port—e.g., a Telnet port—in which case parsed and/or summarized log data from the log-producing device associated with the system's Telnet port(s) would be sought.
  • Similarly, as shown at block 404, the user may select the time period to be covered by the report. The order of blocks 402 and 404 may be reversed in some embodiments or all of the selections may be made at one time on one query screen.
  • At block 406, the process identifies the particular log data analyzer(s) whose databases need to be queried in order to compile the report requested by the user. In one preferred embodiment, this determination is accomplished by a table look up on the raw log server, but this information may be stored elsewhere, including the management station itself. At block 408, a database query (or queries in the case of multiple log data analyzers) is formulated and sent to the log data analyzer(s) hosting the database(s) of interest identified in block 406. Each queried log data analyzer on the system will then respond by sending a database report of parsed and/or summarized log data corresponding to the time period selected. The reports are received by the management station at block 410.
  • As shown at decision diamond 412, a determination may be made of whether a plurality of reports has been received. If so, the management station may then merge the various reports received (at block 414) into a single report and print, display and/or store the merged report at the management station (block 416).
  • A log data analyzer (105, 111 and/or 112) may, in certain embodiments, store summarized log data in a database and respond to queries from a centralized management station. One such process may include: receiving raw log data in a log data analyzer; parsing the raw log data; summarizing the parsed log data; storing the summarized data in a database maintained by the log data analyzer; receiving a database query from a management station; generating a database report in the log data analyzer from the summarized data in response to the query received from the management station; and, sending the database report to the management station. The database report may include the time period of the summarized data and the data in the report may be sorted by the time period of the summarized data. At the option of the user, the data in the report may be limited by the time period of the summarized data.
  • While the exemplary log-producing devices in this description have been firewalls and routers, and the log data has related to networking operations, it is to be understood that other of the many log-producing devices, such as mail servers and the like, and other log data, such as operation status, errors and other events, could be used according to the present invention.
  • While the present invention has been described with respect to a limited number of embodiments, those skilled in the art will appreciate numerous modifications and variations therefrom. It is intended that the appended claims cover all such modifications and variations as fall within the true spirit and scope of this present invention.

Claims (8)

1. A method for processing log data from a plurality of log-producing devices which is stored as sunmarized log data in a plurality of log data analyzers, the method comprising:
formulating database queries in a management station;
sending database queries from the management station to a plurality of log data analyzers;
receiving in the management station a plurality of reports from the plurality of log data analyzers; and
combining in the management station the plurality of reports into a single report.
2. A method for processing log data from a plurality of log-producing devices which is stored as summarized log data in a plurality of log data analyzers, the method comprising:
associating a database query with a certain log data analyzer;
sending a database query from a management station to the certain log data analyzer;
receiving in the management station a report from a database maintained by the certain log data analyzer; and,
displaying the report on the management station.
3. A method for processing log data from a plurality of log-producing devices which is stored as summarized log data in a plurality of log data analyzers, the method comprising:
associating a database query with certain of the plurality of log data analyzers;
sending database queries from a management station to each of the certain log data analyzers;
receiving in the management station a plurality of reports from databases maintained by the certain log data analyzers;
merging the plurality of reports into a single report; and,
displaying the merged report on the management station.
4. A method as recited in claim 3 wherein associating a database query with a certain log data analyzer is performed by table look up on a raw log server.
5. A data processing system for processing log data from a plurality of log-producing devices which comprises:
a plurality of log data analyzers storing summarized log data; and,
a management station connected to the plurality of log data analyzers via data communications links and which
formulates database queries;
sends database queries to a plurality of log data analyzers;
receives a plurality of reports from the plurality of log data analyzers; and
combines the plurality of reports into a single report.
6. A data processing system for processing log data from a plurality of log-producing devices which comprises:
a plurality of log data analyzers storing summarized log data; and,
a management station connected to the plurality of log data analyzers via data communications links and which
associates a database query with a certain log data analyzer;
sends a database query to the certain log data analyzer;
receives a report from a database maintained by the certain log data analyzer; and,
displays the report.
7. A data processing system for processing log data from a plurality of log-producing devices which comprises:
a plurality of log data analyzers storing summarized log data; and,
a management station in data communication with the plurality of log data analyzers and which
associates a database query with certain of the plurality of log data analyzers;
sends database queries to each of the certain log data analyzers;
receives a plurality of reports from databases maintained by the certain log data analyzers;
merges the plurality of reports into a single report; and,
displays the merged report.
8. A data processing system as recited in claim 7 wherein the management station associates a database query with certain of the plurality of log data analyzers by table look up on a raw log server.
US10/898,016 2003-11-26 2004-07-23 Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system Abandoned US20050114505A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US10/898,016 US20050114505A1 (en) 2003-11-26 2004-07-23 Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system
US13/536,720 US9298691B2 (en) 2003-11-26 2012-06-28 Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US52546503P 2003-11-26 2003-11-26
US52540103P 2003-11-26 2003-11-26
US10/898,016 US20050114505A1 (en) 2003-11-26 2004-07-23 Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US13/536,720 Division US9298691B2 (en) 2003-11-26 2012-06-28 Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system

Publications (1)

Publication Number Publication Date
US20050114505A1 true US20050114505A1 (en) 2005-05-26

Family

ID=34595965

Family Applications (2)

Application Number Title Priority Date Filing Date
US10/898,016 Abandoned US20050114505A1 (en) 2003-11-26 2004-07-23 Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system
US13/536,720 Active 2024-09-24 US9298691B2 (en) 2003-11-26 2012-06-28 Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system

Family Applications After (1)

Application Number Title Priority Date Filing Date
US13/536,720 Active 2024-09-24 US9298691B2 (en) 2003-11-26 2012-06-28 Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system

Country Status (1)

Country Link
US (2) US20050114505A1 (en)

Cited By (30)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050125807A1 (en) * 2003-12-03 2005-06-09 Network Intelligence Corporation Network event capture and retention system
US20060036660A1 (en) * 2004-08-13 2006-02-16 Lynn Joseph B System and method for variable block logging with log-ahead buffers
US20060129893A1 (en) * 2004-11-30 2006-06-15 Smith Alan R Apparatus, system, and method for criteria driven summarization of trace entry data
US20070156786A1 (en) * 2005-12-22 2007-07-05 International Business Machines Corporation Method and apparatus for managing event logs for processes in a digital data processing system
US20090210937A1 (en) * 2008-02-15 2009-08-20 Alexander Kraft Captcha advertising
WO2012027691A2 (en) * 2010-08-26 2012-03-01 Unisys Corporation Graphical user interface system for a log analyzer
US20130151560A1 (en) * 2010-07-12 2013-06-13 Sap Ag Systems and Methods for Secure Access of Data
US8903836B2 (en) 2003-11-26 2014-12-02 Tibco Software Inc. System and method for parsing, summarizing and reporting log data
CN104301240A (en) * 2013-07-19 2015-01-21 腾讯科技（深圳）有限公司 Data transmission method and system
US20160080572A1 (en) * 2014-09-15 2016-03-17 Verizon Patent And Licensing, Inc. Call drop intelligent engine
US9298691B2 (en) 2003-11-26 2016-03-29 Tibco Software Inc. Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system
US20160246783A1 (en) * 2015-02-24 2016-08-25 CENX, Inc. Systems and methods for managing data related to network elements from multiple sources
US9521052B1 (en) * 2013-12-20 2016-12-13 Vce Company, Llc Methods, systems, and computer readable mediums for utilizing application programming interfaces for accessing key performance indicator information
US20170093953A1 (en) * 2015-09-28 2017-03-30 Canon Kabushiki Kaisha Information processing apparatus, system, information processing method, and storage medium
US10104108B2 (en) * 2014-03-31 2018-10-16 Lac Co., Ltd. Log analysis system
CN108959659A (en) * 2018-08-14 2018-12-07 杭州安恒信息技术股份有限公司 A kind of log access parsing method and system of big data platform
US20190286719A1 (en) * 2018-03-19 2019-09-19 Vmware Inc. Asynchronous queries on secondary data cores in a distributed computing system
US10491532B2 (en) * 2011-06-27 2019-11-26 International Business Machines Corporation Configurable pacing for messaging systems
CN111597572A (en) * 2020-05-20 2020-08-28 贵州电网有限责任公司 Method and system for managing and consulting transformer substation drawing files
CN112437058A (en) * 2020-11-11 2021-03-02 中国电子科技集团公司第三十研究所 Firewall security policy automatic generation method based on session flow log
US11016972B2 (en) 2018-01-26 2021-05-25 Vmware, Inc. Splitting a time-range query into multiple sub-queries for serial execution
US11016971B2 (en) 2018-01-26 2021-05-25 Vmware, Inc. Splitting a time-range query into multiple sub-queries for parallel execution
US11178213B2 (en) 2018-02-28 2021-11-16 Vmware, Inc. Automated configuration based deployment of stream processing pipeline
US11190401B2 (en) 2018-02-28 2021-11-30 Vmware Inc. Impartial buffering in stream processing
CN114500253A (en) * 2022-01-13 2022-05-13 北京特立信电子技术股份有限公司 Log information storage method and storage medium
US20220321543A1 (en) * 2014-06-02 2022-10-06 iDevices, LLC Systems and methods for secure communication over a network using a linking address
US11514032B2 (en) 2018-01-26 2022-11-29 Vmware, Inc. Splitting a query into native query operations and post-processing operations
US11586623B2 (en) 2018-02-28 2023-02-21 Vmware, Inc. Efficient time-range queries on databases in distributed computing systems
US11620264B2 (en) * 2021-08-27 2023-04-04 Rohde & Schwarz Gmbh & Co. Kg Log file processing apparatus and method for processing log file data
US11741124B2 (en) 2018-01-26 2023-08-29 Vmware, Inc. Data ingestion by distributed-computing systems

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9699040B2 (en) * 2014-09-30 2017-07-04 Vivint, Inc. Systems and methods for monitoring globally distributed remote storage devices
CN110515913B (en) * 2019-08-02 2022-08-09 北京互金新融科技有限公司 Log processing method and device
US11356345B2 (en) * 2020-10-14 2022-06-07 Gigasheet, Inc. Networking data analysis in a visual spreadsheet
CN113570201A (en) * 2021-06-30 2021-10-29 北京达佳互联信息技术有限公司 Data processing method, device, equipment, storage medium and program product

Citations (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5627886A (en) * 1994-09-22 1997-05-06 Electronic Data Systems Corporation System and method for detecting fraudulent network usage patterns using real-time network monitoring
US5787253A (en) * 1996-05-28 1998-07-28 The Ag Group Apparatus and method of analyzing internet activity
US5886643A (en) * 1996-09-17 1999-03-23 Concord Communications Incorporated Method and apparatus for discovering network topology
US6134591A (en) * 1997-06-18 2000-10-17 Client/Server Technologies, Inc. Network security and integration method and system
US20020046273A1 (en) * 2000-01-28 2002-04-18 Lahr Nils B. Method and system for real-time distributed data mining and analysis for network
US20020062237A1 (en) * 2000-08-04 2002-05-23 Scott Matsumoto Transactional monitoring system and method
US20020138762A1 (en) * 2000-12-01 2002-09-26 Horne Donald R. Management of log archival and reporting for data network security systems
US6484203B1 (en) * 1998-11-09 2002-11-19 Sri International, Inc. Hierarchical event monitoring and analysis
US20030037136A1 (en) * 2001-06-27 2003-02-20 Labovitz Craig H. Method and system for monitoring control signal traffic over a computer network
US20030120593A1 (en) * 2001-08-15 2003-06-26 Visa U.S.A. Method and system for delivering multiple services electronically to customers via a centralized portal architecture
US6714977B1 (en) * 1999-10-27 2004-03-30 Netbotz, Inc. Method and system for monitoring computer networks and equipment
US6836894B1 (en) * 1999-07-27 2004-12-28 International Business Machines Corporation Systems and methods for exploratory analysis of data for event management
US20050114508A1 (en) * 2003-11-26 2005-05-26 Destefano Jason M. System and method for parsing, summarizing and reporting log data
US20050125807A1 (en) * 2003-12-03 2005-06-09 Network Intelligence Corporation Network event capture and retention system
US7031981B1 (en) * 2001-12-21 2006-04-18 Unisys Corporation Tool supporting system log file reporting
US7099884B2 (en) * 2002-12-06 2006-08-29 Innopath Software System and method for data compression and decompression
US20060265746A1 (en) * 2001-04-27 2006-11-23 Internet Security Systems, Inc. Method and system for managing computer security information
US7181766B2 (en) * 2000-04-12 2007-02-20 Corente, Inc. Methods and system for providing network services using at least one processor interfacing a base network
US7219239B1 (en) * 2002-12-02 2007-05-15 Arcsight, Inc. Method for batching events for transmission by software agent
US7231403B1 (en) * 2002-11-15 2007-06-12 Messageone, Inc. System and method for transformation and analysis of messaging data
US7246156B2 (en) * 2003-06-09 2007-07-17 Industrial Defender, Inc. Method and computer program product for monitoring an industrial network

Family Cites Families (23)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5606693A (en) 1991-10-02 1997-02-25 International Business Machines Corporation Distributed database management over a network
JPH0836513A (en) 1993-12-29 1996-02-06 Xerox Corp Data management method and restoration method of data-management error
US5903898A (en) 1996-06-04 1999-05-11 Oracle Corporation Method and apparatus for user selectable logging
US5832508A (en) 1996-09-18 1998-11-03 Sybase, Inc. Method for deallocating a log in database systems
US6321234B1 (en) 1996-09-18 2001-11-20 Sybase, Inc. Database server system with improved methods for logging transactions
US6073172A (en) 1997-07-14 2000-06-06 Freegate Corporation Initializing and reconfiguring a secure network interface
US6052694A (en) 1998-03-18 2000-04-18 Electronic Data Systems Corporation Method and apparatus for logging database performance characteristics
US6381628B1 (en) 1998-10-02 2002-04-30 Microsoft Corporation Summarized application profiling and quick network profiling
US6530024B1 (en) 1998-11-20 2003-03-04 Centrax Corporation Adaptive feedback security system and method
US6754214B1 (en) 1999-07-19 2004-06-22 Dunti, Llc Communication network having packetized security codes and a system for detecting security breach locations within the network
US6289455B1 (en) 1999-09-02 2001-09-11 Crypotography Research, Inc. Method and apparatus for preventing piracy of digital content
US6618822B1 (en) 2000-01-03 2003-09-09 Oracle International Corporation Method and mechanism for relational access of recovery logs in a database system
US6785666B1 (en) 2000-07-11 2004-08-31 Revenue Science, Inc. Method and system for parsing navigation information
CA2382714A1 (en) 2002-04-19 2003-10-19 Ibm Canada Limited-Ibm Canada Limitee Substituting parameter markers for literals in a database query language statement to promote reuse of previously generated access plans
US7346526B2 (en) 2002-10-16 2008-03-18 Ita Software, Inc. System and method for entering flexible travel queries with layover description
US7043505B1 (en) * 2003-01-28 2006-05-09 Unisys Corporation Method variation for collecting stability data from proprietary systems
US7155460B2 (en) 2003-03-18 2006-12-26 Network Appliance, Inc. Write-once-read-many storage system and method for implementing the same
US7103772B2 (en) 2003-05-02 2006-09-05 Giritech A/S Pervasive, user-centric network security enabled by dynamic datagram switch and an on-demand authentication and encryption scheme through mobile intelligent data carriers
US7599939B2 (en) 2003-11-26 2009-10-06 Loglogic, Inc. System and method for storing raw log data
US20050114321A1 (en) 2003-11-26 2005-05-26 Destefano Jason M. Method and apparatus for storing and reporting summarized log data
US20050114706A1 (en) 2003-11-26 2005-05-26 Destefano Jason Michael System and method for the collection and transmission of log data over a wide area network
US20050114707A1 (en) 2003-11-26 2005-05-26 Destefano Jason Michael Method for processing log data from local and remote log-producing devices
US20050114505A1 (en) 2003-11-26 2005-05-26 Destefano Jason M. Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system

Patent Citations (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5627886A (en) * 1994-09-22 1997-05-06 Electronic Data Systems Corporation System and method for detecting fraudulent network usage patterns using real-time network monitoring
US5787253A (en) * 1996-05-28 1998-07-28 The Ag Group Apparatus and method of analyzing internet activity
US5886643A (en) * 1996-09-17 1999-03-23 Concord Communications Incorporated Method and apparatus for discovering network topology
US6134591A (en) * 1997-06-18 2000-10-17 Client/Server Technologies, Inc. Network security and integration method and system
US6484203B1 (en) * 1998-11-09 2002-11-19 Sri International, Inc. Hierarchical event monitoring and analysis
US6836894B1 (en) * 1999-07-27 2004-12-28 International Business Machines Corporation Systems and methods for exploratory analysis of data for event management
US6714977B1 (en) * 1999-10-27 2004-03-30 Netbotz, Inc. Method and system for monitoring computer networks and equipment
US20020046273A1 (en) * 2000-01-28 2002-04-18 Lahr Nils B. Method and system for real-time distributed data mining and analysis for network
US7181766B2 (en) * 2000-04-12 2007-02-20 Corente, Inc. Methods and system for providing network services using at least one processor interfacing a base network
US20020062237A1 (en) * 2000-08-04 2002-05-23 Scott Matsumoto Transactional monitoring system and method
US20020138762A1 (en) * 2000-12-01 2002-09-26 Horne Donald R. Management of log archival and reporting for data network security systems
US20060265746A1 (en) * 2001-04-27 2006-11-23 Internet Security Systems, Inc. Method and system for managing computer security information
US20030037136A1 (en) * 2001-06-27 2003-02-20 Labovitz Craig H. Method and system for monitoring control signal traffic over a computer network
US20030120593A1 (en) * 2001-08-15 2003-06-26 Visa U.S.A. Method and system for delivering multiple services electronically to customers via a centralized portal architecture
US7031981B1 (en) * 2001-12-21 2006-04-18 Unisys Corporation Tool supporting system log file reporting
US7231403B1 (en) * 2002-11-15 2007-06-12 Messageone, Inc. System and method for transformation and analysis of messaging data
US7219239B1 (en) * 2002-12-02 2007-05-15 Arcsight, Inc. Method for batching events for transmission by software agent
US7099884B2 (en) * 2002-12-06 2006-08-29 Innopath Software System and method for data compression and decompression
US7246156B2 (en) * 2003-06-09 2007-07-17 Industrial Defender, Inc. Method and computer program product for monitoring an industrial network
US20050114508A1 (en) * 2003-11-26 2005-05-26 Destefano Jason M. System and method for parsing, summarizing and reporting log data
US20050125807A1 (en) * 2003-12-03 2005-06-09 Network Intelligence Corporation Network event capture and retention system

Cited By (48)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8903836B2 (en) 2003-11-26 2014-12-02 Tibco Software Inc. System and method for parsing, summarizing and reporting log data
US9298691B2 (en) 2003-11-26 2016-03-29 Tibco Software Inc. Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system
US8676960B2 (en) 2003-12-03 2014-03-18 Emc Corporation Network event capture and retention system
US20070011308A1 (en) * 2003-12-03 2007-01-11 Network Intelligence Corporation Network event capture and retention system
US20050125807A1 (en) * 2003-12-03 2005-06-09 Network Intelligence Corporation Network event capture and retention system
US20070011306A1 (en) * 2003-12-03 2007-01-11 Network Intelligence Corporation Network event capture and retention system
US20070011310A1 (en) * 2003-12-03 2007-01-11 Network Intelligence Corporation Network event capture and retention system
US20070011309A1 (en) * 2003-12-03 2007-01-11 Network Intelligence Corporation Network event capture and retention system
US9438470B2 (en) 2003-12-03 2016-09-06 Emc Corporation Network event capture and retention system
US9401838B2 (en) 2003-12-03 2016-07-26 Emc Corporation Network event capture and retention system
US20070011305A1 (en) * 2003-12-03 2007-01-11 Network Intelligence Corporation Network event capture and retention system
US9720911B2 (en) 2004-08-13 2017-08-01 Ca, Inc. System and method for variable block logging with log-ahead buffers
US8090691B2 (en) 2004-08-13 2012-01-03 Computer Associates Think, Inc. System and method for variable block logging with log-ahead buffers
US20060036660A1 (en) * 2004-08-13 2006-02-16 Lynn Joseph B System and method for variable block logging with log-ahead buffers
US20060129893A1 (en) * 2004-11-30 2006-06-15 Smith Alan R Apparatus, system, and method for criteria driven summarization of trace entry data
US20070156786A1 (en) * 2005-12-22 2007-07-05 International Business Machines Corporation Method and apparatus for managing event logs for processes in a digital data processing system
US20090210937A1 (en) * 2008-02-15 2009-08-20 Alexander Kraft Captcha advertising
US9002868B2 (en) * 2010-07-12 2015-04-07 Sap Se Systems and methods for secure access of data
US20130151560A1 (en) * 2010-07-12 2013-06-13 Sap Ag Systems and Methods for Secure Access of Data
WO2012027691A3 (en) * 2010-08-26 2012-05-03 Unisys Corporation Graphical user interface system for a log analyzer
WO2012027691A2 (en) * 2010-08-26 2012-03-01 Unisys Corporation Graphical user interface system for a log analyzer
US10491532B2 (en) * 2011-06-27 2019-11-26 International Business Machines Corporation Configurable pacing for messaging systems
CN104301240A (en) * 2013-07-19 2015-01-21 腾讯科技（深圳）有限公司 Data transmission method and system
US9521052B1 (en) * 2013-12-20 2016-12-13 Vce Company, Llc Methods, systems, and computer readable mediums for utilizing application programming interfaces for accessing key performance indicator information
US10104108B2 (en) * 2014-03-31 2018-10-16 Lac Co., Ltd. Log analysis system
US20220321543A1 (en) * 2014-06-02 2022-10-06 iDevices, LLC Systems and methods for secure communication over a network using a linking address
US20160080572A1 (en) * 2014-09-15 2016-03-17 Verizon Patent And Licensing, Inc. Call drop intelligent engine
US10003492B2 (en) * 2015-02-24 2018-06-19 CENX, Inc. Systems and methods for managing data related to network elements from multiple sources
US20160246783A1 (en) * 2015-02-24 2016-08-25 CENX, Inc. Systems and methods for managing data related to network elements from multiple sources
US20170093953A1 (en) * 2015-09-28 2017-03-30 Canon Kabushiki Kaisha Information processing apparatus, system, information processing method, and storage medium
US10545944B2 (en) * 2015-09-28 2020-01-28 Canon Kabushiki Kaisha Information processing apparatus for generating statistic information to recognize when an unsuccessfully-transmitted file exists
US11016971B2 (en) 2018-01-26 2021-05-25 Vmware, Inc. Splitting a time-range query into multiple sub-queries for parallel execution
US11741124B2 (en) 2018-01-26 2023-08-29 Vmware, Inc. Data ingestion by distributed-computing systems
US11593365B2 (en) 2018-01-26 2023-02-28 Vmware, Inc. Splitting a time-range query into multiple sub-queries for serial execution
US11514032B2 (en) 2018-01-26 2022-11-29 Vmware, Inc. Splitting a query into native query operations and post-processing operations
US11016972B2 (en) 2018-01-26 2021-05-25 Vmware, Inc. Splitting a time-range query into multiple sub-queries for serial execution
US11178213B2 (en) 2018-02-28 2021-11-16 Vmware, Inc. Automated configuration based deployment of stream processing pipeline
US11190401B2 (en) 2018-02-28 2021-11-30 Vmware Inc. Impartial buffering in stream processing
US11586623B2 (en) 2018-02-28 2023-02-21 Vmware, Inc. Efficient time-range queries on databases in distributed computing systems
US20210224226A1 (en) * 2018-03-19 2021-07-22 Vmware Inc. Asynchronous queries on secondary data cores in a distributed computing system
US20190286719A1 (en) * 2018-03-19 2019-09-19 Vmware Inc. Asynchronous queries on secondary data cores in a distributed computing system
US10949390B2 (en) * 2018-03-19 2021-03-16 Vmware Inc. Asynchronous queries on secondary data cores in a distributed computing system
US11755356B2 (en) * 2018-03-19 2023-09-12 Vmware Inc. Asynchronous queries on secondary data cores in a distributed computing system
CN108959659A (en) * 2018-08-14 2018-12-07 杭州安恒信息技术股份有限公司 A kind of log access parsing method and system of big data platform
CN111597572A (en) * 2020-05-20 2020-08-28 贵州电网有限责任公司 Method and system for managing and consulting transformer substation drawing files
CN112437058A (en) * 2020-11-11 2021-03-02 中国电子科技集团公司第三十研究所 Firewall security policy automatic generation method based on session flow log
US11620264B2 (en) * 2021-08-27 2023-04-04 Rohde & Schwarz Gmbh & Co. Kg Log file processing apparatus and method for processing log file data
CN114500253A (en) * 2022-01-13 2022-05-13 北京特立信电子技术股份有限公司 Log information storage method and storage medium

Also Published As

Publication number Publication date
US20130144894A1 (en) 2013-06-06
US9298691B2 (en) 2016-03-29

Similar Documents

Publication Publication Date Title
US7599939B2 (en) System and method for storing raw log data
US9298691B2 (en) Method and apparatus for retrieving and combining summarized log data in a distributed log data processing system
US20050114707A1 (en) Method for processing log data from local and remote log-producing devices
US20050114321A1 (en) Method and apparatus for storing and reporting summarized log data
US20050114706A1 (en) System and method for the collection and transmission of log data over a wide area network
US11757740B2 (en) Aggregation of select network traffic statistics
US5787253A (en) Apparatus and method of analyzing internet activity
US9009139B2 (en) Query pipeline
US7895158B2 (en) Data logging in content routed networks
US20070230486A1 (en) Communication and compliance monitoring system
US9678921B2 (en) Method and apparatus for data transfer reconciliation
US20060028999A1 (en) Flows based visualization of packet networks with network performance analysis, troubleshooting, optimization and network history backlog
US20160191549A1 (en) Rich metadata-based network security monitoring and analysis
US20050114508A1 (en) System and method for parsing, summarizing and reporting log data
US20130290521A1 (en) Method and system for annotating network flow information
US20080034049A1 (en) System and Method for the Capture and Archival of Electronic Communications
Collins et al. Network security through data analysis: building situational awareness
US20140208420A1 (en) System for remotely monitoring status information of devices connected to a network
US20020144156A1 (en) Network port profiling
US20100325178A1 (en) Creating and/or managing meta-data for data storage devices using a packet switch appliance
WO2002061510A2 (en) Network port profiling
CN107645480B (en) Data monitoring method, system and device
CN106899443A (en) The acquisition method and equipment of a kind of Netflow datas on flows
US11190417B2 (en) Methods, systems, and computer readable media for processing network flow metadata at a network packet broker
US7266088B1 (en) Method of monitoring and formatting computer network data

Legal Events

Date Code Title Description
AS Assignment

Owner name: LOGLOGIC, INC., CALIFORNIA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:DESTEFANO, JASON MICHAEL;MOJSA, TOMASZ MARIUSZ;GRABOWSKI, THOMAS HUNT SCHABO;REEL/FRAME:015949/0805

Effective date: 20040901

STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION

AS Assignment

Owner name: TIBCO SOFTWARE INC., CALIFORNIA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:LOGLOGIC, INC.;REEL/FRAME:030560/0473

Effective date: 20120411

AS Assignment

Owner name: CLOUD SOFTWARE GROUP, INC., FLORIDA

Free format text: CHANGE OF NAME;ASSIGNOR:TIBCO SOFTWARE INC.;REEL/FRAME:062714/0634

Effective date: 20221201