CN100490392C - A garbage mail processing system and garbage mail sorting method - Google Patents
A garbage mail processing system and garbage mail sorting method Download PDFInfo
- Publication number
- CN100490392C CN100490392C CNB2006100351554A CN200610035155A CN100490392C CN 100490392 C CN100490392 C CN 100490392C CN B2006100351554 A CNB2006100351554 A CN B2006100351554A CN 200610035155 A CN200610035155 A CN 200610035155A CN 100490392 C CN100490392 C CN 100490392C
- Authority
- CN
- China
- Prior art keywords
- degree
- belief
- spam
- mailbox
- 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.)
- Active
Links
Images
Abstract
The related garbage mail process system compromises: a garbage mail filter module in SMTP, a virus analysis module, a mail-box monitor 1, a trust database 2, and a trustness level judgment module 3 for calling the trustness value and comparing with the reference value, wherein the filter module modifies the mail trustness value according to all other process results. This invention improves system process capacity, and enhances protection on illegal access.
Description
Technical field
The present invention relates to the treatment technology in the electronic information transmission, particularly relate to processing to spam, go-on-go and effective strick precaution of malice visitor.
Technical background
Along with the arrival of network information society, spam is perplexing the manager of mailbox server and vast user always.In order to remove increasing spam, the manager of mailbox server has designed auditing system white, blacklist pipes off blamable email address and domain name, will the absolute white list of listing in trusty, thus can the fast processing mail.Existing white, blacklist technology can not effectively must solve the situation of black and white lists dynamic change too in absolutization.If a spam outbox person utilizes the mailbox of stealing (white list mailbox) to send out spam, or white list subscriber set unusual (poisoning or middle wooden horse), so white, blacklist can bring serious counter productive on the contrary.Existing member address white, blacklist produces too manually changes the problem that not can solve automatic generation and augment at any time.
Also in mailbox server STMP, be provided with overanxious system of spam or virus analysis system in the prior art, can effectively tackle the mail of various violation keywords and suspect code appearance, but can not make cocksure conclusion the mail that passes through.Existing mail filtering system too disperses (black, white list, spam filters, virus filter is independently running separately), can not whether reliably produce a dynamic comprehensive overall assessment to destination object is current, can't come evaluation object, judge with the combined influence of time.Be that the time combined influence is judged and can't be embodied in existing mail filtering system.
Existing filter just utilizes the other feature of interior perhaps structural area of normal email, spam to filter.If the processing attitude feature that can utilize the addressee to treat normal email, spam influences filtering decision process, then can improve the performance of whole filtration system greatly.But existing mail filtering system there is no this ability.
Summary of the invention
The object of the invention basic dependence of generation black, white list in solving existing spam processing is manually finished, can't adapt to problem black, the white list dynamic change, and spam gets interim dynamic random characteristics, cause the malice sender by effectively intercepting of blacklist can not be permanent problem.
For addressing the above problem, the invention provides a kind of spam treatment system, this system comprises twit filter module, the virus analysis device module that is arranged in the SMTP mail server, also comprises:
(1) mailbox monitor module is used for the processing behavioural characteristic to normal email, two kinds of different mails of spam according to the mailbox owner, the degree of belief numerical value of rising or reduction source of email address;
(2) record the degree of belief database that mail is trusted number of degrees value by addresses of items of mail; And
(3) degree of belief is passed judgment on module, and this module is called corresponding source address by the address of mail from the degree of belief database degree of belief numerical value is compared with setting range, greater than the normal email that is judged to be more than the setting range maximum, mail-sorting is gone into normal mailbox; Less than the spam that is judged to be below the setting range minimum value, mail-sorting is gone into the rubbish mailbox; Drop on the current mail between the maximin of setting range, mail to the twit filter module and the virus filter module is carried out virus filtration, filter for wherein arbitrary time defectively, then mail is sent to the rubbish mailbox; If two-layer filtration is all passed through, then from the degree of belief database, access the degree of belief numerical value of corresponding source address again, trust judgement relatively, the normal email that is judged to be greater than the default median of degree of belief, deliver to normal mailbox, the spam that is judged to be less than the default median of degree of belief sends to the rubbish mailbox;
The mailbox monitor module is according to the twit filter module, virus analysis device module, and degree of belief is passed judgment on the result of module to mail, revise the degree of belief numerical value of the source of email address correspondence of this mail of storing in the degree of belief database, reduction is the degree of belief value of the source of email address correspondence of spam by go-on-go, and raising by go-on-go is the degree of belief value of the source of email address correspondence of normal email.
Preferably, the mode of described degree of belief judge module judge is that utmost good faith is judged and relative trust is judged.
Preferably, store the degree of belief relation data of territory level in the degree of belief database;
The ruling scope of mailbox monitor module is the territory at addresses of items of mail place, and promptly the mail monitor module is collected the addresses of items of mail of transmitting current mail, and according to the degree of belief data of the go-on-go results modification of current mail being transmitted the addresses of items of mail of current mail.
Among the present invention, mail degree of belief decision-making system in the spam treatment system, evaluation mechanism with reference to the personal credit of using for reference society, set up a cover to the source of email address, the comprehensive assessment mechanism in territory, remove and include conventional garbage filtrating mail engine, the anti-virus engine to the source address, outside the evaluation influence in territory, also Promethean joining day combined influence, the addressee treats normal email, the mailbox surveillance of the processing attitude feature affects of spam, and on two levels of utmost good faith judgement and relative trust judgement, mail is trusted judgement, trust the degrees of data storehouse to reach the mail with time and historical summation formation, in fact it is a dynamic data base that includes the black and white lists of automatic generation.In above system, Spam filtering system, virus analysis system, the mailbox surveillance all is the degree of belief adjudicator.Judgement each time all can be trusted the degrees of data storehouse to mail and be exerted an influence, and makes its continual renovation, has significant support effect to stopping spam accurately.
The present invention also provides a kind of method of go-on-go spam, and that the system that this method is used comprises is black, white list auditing module, twit filter module, virus analysis device module, and the method comprising the steps of:
(1) the degree of belief numerical value of finding out corresponding source address by the address of mail from the degree of belief database is compared with setting range, greater than the peaked normal email that is judged to be of setting range, mail-sorting is gone into normal mailbox; Less than the spam that is judged to be of setting range minimum value, mail-sorting is gone into the rubbish mailbox; Drop on and carry out step (2) between the maximin of setting range;
(2) do further go-on-go processing through twit filter module and virus analysis device module, filter in the go-on-go processing procedure at twice, anyly once filter defectively, then mail is judged to be spam, go-on-go is to the rubbish mailbox, and twice filtration is all qualified carries out step (3);
(3) again from comparing with accessing the degree of belief numerical value of corresponding source address and the mean value of setting range maximin the degree of belief database, mail greater than this mean value is judged to be normal email, mail-sorting is gone into normal mailbox, mail less than this mean value is judged to be spam, and mail-sorting is gone into the rubbish mailbox;
(4) by result to mail treatment, the degree of belief value of source of email address correspondence in the revision degree of belief database, the degree of belief value of address, increase normal email source correspondence, the degree of belief value of address, minimizing spam source correspondence.
Preferably, the step of the degree of belief value of source of email address correspondence also comprises in the revision degree of belief database:
Foundation increases and decreases the degree of belief value of other addresses of items of mail of the current mail of forwarding that obtains to the increase and decrease of the degree of belief value of current source of email address correspondence.
Good effect of the present invention is in mail server destination object to be formed the evaluation system of an effective global trust degree, with the mail degree of belief, be actually the degree of reliability that the degree of belief evaluation with the sender gets the mail, can debate in the knowledge system effective must the raising at existing mail and filter the interception rate and reduce False Rate.Prior meaning is that evaluation system changes with dynamic credit rating and replaces absolute black and white lists that higher adaptive ability is arranged, and can adapt to the email environment of dynamic change, can solve the problem that the auto black and white list generates difficulty again.System can embody the influence of historical time cumulative effect, the cumulative effect of historical time can make the degree of belief trend of destination object can correctly to express its whether reliably level, so can offer an explanation mail more accurately, and this evil of people principle is more suitable for having in filtration the spam of dynamic sender's feature.In this mail degree of belief decision-making system, handle the attitude feature with the people to the different emotions of normal email, spam judge influence comprehensive the adding, than existing systems scientific and effective more.To the cumulative function in territory, the application with transmitting principle helps at a Security Target object of system-level quick formation trusting relationship net under long-time the application, makes spam originator be difficult to more infiltrate.
Description of drawings
Fig. 1 is the diagram of carrying out the mail judgement according to the mailbox degree of belief value in the supporting database.
Fig. 2 is in the spam treatment system, realizes the schematic diagram that trust evaluation and mail are judged.
Fig. 3 is the schematic diagram of go-on-go spam of the present invention.
Fig. 4 is that monitor module expands the example that the territory level monitors to.
Among the figure, 1 utmost good faith judgement, 2 twit filter modules, 3 virus filter modules, 4 mail monitor modules, 5 are trusted judgement, 6 degree of belief databases, 7 normal mailboxes, 8 rubbish mailboxes, A9 user, B10 user, C11 user, 12 receiver system usings relatively.
Embodiment
Further specify below in conjunction with accompanying drawing and the objective of the invention is how to realize.
For simpler and clearer, clearly state that summary of the invention at first introduces proprietary term.
Mail degree of belief: the credibility that is used for role of delegate object (concerning mailing system, effective object is sender or outbox territory).The low more then effective object of mail degree of belief value is unreliable more, otherwise, high more then reliable more.In this mail degree of belief decision-making system, the possible probability that reliably refers to normal email is reliable more, and it is the probability height of normal email, otherwise it is that the probability of normal email is low more.In the mail belief system, be that principle is based on the lower and frequent address substitute of spammer degree of belief with this evil of people.
Degree of belief adjudicator: in the degree of belief decision-making system, trust the role that the adjudicator serves as judge, can judge to all behaviors.Ruling to behavior is qualitative, can produce court verdict, directly the change of the degree of belief numerical value of influence object.
Trust judgement: by trusting whether the adjudicator violates credit to the behavior of destination object once judgement, can produce legal or illegal, can't judge three kinds of exercising results to destination object, corresponding respectively credit rating increases, credit rating declines to a great extent, the constant three kinds of credit rating value result of variations of credit rating.Through trusting the long-term accumulated effect of judgement, make the mail degree of belief of effective object trends towards correctly expressing whether it reliable.
Trust to judge: whether a reliable assessment of making is judged to its certain mail behavior according to the degree of belief of current goal object by the degree of belief decision-making system, divides utmost good faith to judge and two kinds of relative trust judgements.
Utmost good faith is judged: be the degree of belief according to destination object, absolute character carried out in its certain behavior judge, produce reliable, unreliable, definite three kinds of results.Be characterized in having only degree of belief very significantly near minimum or maximum, can have significantly showed whether reliably just make reliable or insecure judged result, and all the other are not judged as without exception and determine.
Trust relatively and judge: be degree of belief, whether its certain behavior reliably carried out possibility predict, produce and reliably to predict the outcome for unreliable two kinds with possibility according to destination object.Be characterized in just admitting the side that probability is big, make relative prediction as long as have a kind ofly in reliable and the insecure two kinds of probability greater than the other side.
Referring to Fig. 1.Among Fig. 1, a is the default minimum value of degree of belief, and c is the default maximum of degree of belief, and b is the default median of degree of belief.In the utmost good faith degree is judged, will be judged to be anything but reliably, will be judged to be definitely reliably, between a-c, not be judged to be and determine greater than c less than a.In relatively degree of belief was judged, being judged to be between a-b may be unreliable, being judged to be between b-c may be reliable.
Core of the present invention is: judge with trust evaluation, mail to combine with three kinds of modes of system-level expansion, set up the comprehensive assessment mechanism of a cover to source of email address, territory, remove and comprise existing anti-rubbish mail engine, outside the evaluation influence to address, source, territory of anti-virus engine, also Promethean joining day combined influence, addressee treat the processing attitude feature affects of normal email, spam, and on two levels of utmost good faith judgement and relative trust judgement, mail is judged shunting, to reach than existing better adaptive classification effect.
The present invention relates in the spam treatment system: twit filter module 2, virus filter module 3, mail monitor module 4 and the special degree of belief database 6 that is provided with and the receiver system using 12 of prior art.
Fig. 2 is in the spam treatment system, realizes the schematic diagram that trust evaluation and mail are judged.Wherein, twit filter module 2, virus email filter module 3, mail monitor module 4 judges the whether credible of mail respectively, and with the degree of belief storage in degree of belief database 6, during initial condition, degree of belief is low.
Twit filter module 2 judges by the rubbish filtering engine whether mail is spam, thereby rewards (increase credit rating) judgement with punishment (minimizing credit rating) to source of email address, territory;
Virus email filter module 3 judges by the virus filtration engine whether mail contains suspect code, thereby judgement is rewarded and punished etc. in source of email address, territory.
In conjunction with Fig. 2 and Fig. 3, the branch detecting method to spam among the present invention comprises:
(1) after receiver system using 12 gets the mail, accessing the degree of belief numerical value of corresponding source address by the address of mail from degree of belief database 6, carry out utmost good faith and judge, is example with Fig. 1, if greater than predefined c value, judgement is directly mail to normal mailbox 7, i.e. the destination address mailbox for normal email, if less than predefined a value, then directly send to rubbish mailbox 8, c can be set to the 75%-95% size of 2b as the case may be, and the big more degree of belief of the maximum of setting is high more.The minimum value of setting can be set to the 5%-25% size of 2b as the case may be, and the more little degree of belief of the minimum value of setting is low more.If the degree of belief value of this mail corresponding address is then carried out step (2) between a and c.
(2) with the mail of degree of belief value between a and c, mail to twit filter module 2 and virus filter module 3 is carried out virus filtration, filter for wherein arbitrary time defectively, then mail is sent to rubbish mailbox 8; If two-layer filtration is all passed through, then carry out step (3).
(3) accessing the degree of belief numerical value that accesses corresponding source address in the supporting database 6 again, trust judgement relatively, still is example with Fig. 1, greater than the normal email that is judged to be of b value, deliver to normal mailbox 7, i.e. target mailbox, the spam that is judged to be less than the b value sends to rubbish mailbox 8.
(4) after mail is arrived different mailboxes by go-on-go, mailbox monitor module 4 will be revised its degree of belief value according to the result of mail, and upgrade degree of belief database 6.
Judgement provides support to trusting relationship mailing system shown in Figure 3 to mail on two levels: utmost good faith judgement 1 and relative trust judge 5.Utmost good faith judges 1, play the highest preferential qualitative effect, according to degree of belief to mail behavior classify and judge and shunting, because the condition of its judgement is very harsh, so very high accuracy is arranged, can be used for replacing existing black and white lists technology, and solved the automatic generation problem of black and white lists, with the dynamic self-adapting variation issue.Trust relatively and judge 5, occur in filters and all can't determine that it is under the situation of spam, be lowest priority, do a possibility prediction according to degree of belief to its quality this moment, forms final decision.Two-layer trust is judged, if be with obviously reliable, definitely judges, if not obvious, then in the end carries out forecast assessment, the design that this thought is carried out at once.It judges that in utmost good faith 1 can reach very desirable absolute fine or not classifying quality, and is trusting judgement 5 relatively, then is the means that improve filterability at last.
The result of determination of being made in the go-on-go process is each time all passed through the management software support, the degree of belief value of corresponding address in the degree of belief database 6 is made rewarded or chastening modification;
Modification to degree of belief database 6, be by processing and the mode of operation decision of addressee mailbox owner to normal email, spam, can be that normalized pattern reduces a rule set specifically by the mailbox operation behavior, thereby decision is to the source of email address, or the degree of belief database of posting address is made the judgement that corresponding degree of belief is revised; Automatically generate dynamic black and white lists, promptly be listed in absolute trusted scope or trusted scope anything but.
Among Fig. 4, solid line represents that e-mail sending represents that to, dotted line degree of belief action direction, terminal point increase for the degree of belief of starting point.
In conjunction with Fig. 4, the monitoring range of mail monitor module 4 expands to the transmission of mail, be forwarded to certain user C11 to the mail of certain user B10 transmission through certain user B10 by certain user A9, then make the degree of belief that certain user C11 is trusted to certain user A9 and reward judgement by monitor system, and revise the corresponding degree of belief value of supporting database, thereby form the network of personal connections structure of mutual trust stable between the target mailbox address of safety.
In conjunction with shown in Figure 4,, be the judgement made by the mailbox monitor system according to the operation of transmitting normal email award, thereby the mutual trust that forms between the Security Target object concern filter screen to the source address degree of belief to the correction of degree of belief database 6.System-level expansion that Here it is is based on trusting relationship and expands to whole mail system, the expanded application of spreading over a whole area from one point.Expand as follows: one, all are trusted the territory that the effect of adjudicating runs up to effective object, just can form the trusting relationship of a territory level, extend to system-level application; Two, following asserting done in generation and the effect in order to strengthen trusting relationship, and the object of a trust, the object of its trust also may be reliable.It is acted on the trusting relationship system, the degree of belief of definition effective object has transitive relation: certain user A9 is to certain user B10 post a letter (certain user B10 increases in the degree of belief of certain user A9), certain user B10 is to certain user C11 post a letter (certain user C11 increases in the degree of belief of certain user B10), then this transitive relation can cause producing the effect same (certain user C11 increases in the degree of belief of certain user A9) that certain user A9 posts a letter to certain user C11, and the amplitude of effect is directly proportional with the degree of belief of medium object (certain user B10).This transitive relation is irreversible unidirectional delivery, is made to certain user A9 as the trust arbiter by mailing system the degree of belief of certain user C11 is rewarded.Warp is in transfer function, can aggravate to trust the pace of change of each role trust degree, purpose is to make the network of personal connections structure community that forms a stable mutual trust between the destination object that has safety now, and feasible spam initiation object as the outsider is difficult to permeate more.
The above only is preferred embodiment of the present invention, and not in order to restriction the present invention, all any modifications of being done within the spirit and principles in the present invention are equal to alternative and improvement etc., all should be included in protection scope of the present invention.
Claims (5)
1. spam treatment system, this system comprises twit filter module, the virus analysis device module that is arranged in the SMTP mail server, it is characterized in that: also comprise:
(1) mailbox monitor module is used for the processing behavioural characteristic to normal email, two kinds of different mails of spam according to the mailbox owner, the degree of belief numerical value of rising or reduction source of email address;
(2) record the degree of belief database that mail is trusted number of degrees value by addresses of items of mail; And
(3) degree of belief is passed judgment on module, and this module is called corresponding source address by the address of mail from the degree of belief database degree of belief numerical value is compared with setting range, greater than the normal email that is judged to be more than the setting range maximum, mail-sorting is gone into normal mailbox; Less than the spam that is judged to be below the setting range minimum value, mail-sorting is gone into the rubbish mailbox; Drop on the current mail between the maximin of setting range, mail to the twit filter module and virus analysis device module is carried out virus filtration, filter for wherein arbitrary time defective, then with mail-sorting to the rubbish mailbox; If two-layer filtration is all passed through, then from the degree of belief database, access the degree of belief numerical value of corresponding source address again, compare with the mean value of setting range maximin, mail greater than this mean value is judged to be normal email, mail-sorting is gone into normal mailbox, mail less than this mean value is judged to be spam, and mail-sorting is gone into the rubbish mailbox;
The mailbox monitor module also is used for according to the twit filter module, virus analysis device module, and degree of belief is passed judgment on the result of module to mail, revise the degree of belief numerical value of the source of email address correspondence of this mail of storing in the degree of belief database, reduction is the degree of belief value of the source of email address correspondence of spam by go-on-go, and raising by go-on-go is the degree of belief value of the source of email address correspondence of normal email.
2. a kind of spam treatment system according to claim 1 is characterized in that: the mode that described degree of belief is passed judgment on the module judge is that utmost good faith is judged and relative trust is judged.
3. a kind of spam treatment system according to claim 1 and 2 is characterized in that:
Store the degree of belief relation data of territory level in the degree of belief database;
The ruling scope of mailbox monitor module is the territory at addresses of items of mail place, and promptly the mail monitor module is collected the addresses of items of mail of transmitting current mail, and according to the degree of belief data of the go-on-go results modification of current mail being transmitted the addresses of items of mail of current mail.
4. that the method for a go-on-go spam, the system that this method is used comprise is black, white list auditing module, twit filter module, virus analysis device module, and it is characterized in that: the method comprising the steps of:
(1) the degree of belief numerical value of finding out corresponding source address by the address of mail from the degree of belief database is compared with setting range, greater than the peaked normal email that is judged to be of setting range, mail-sorting is gone into normal mailbox; Less than the spam that is judged to be of setting range minimum value, mail-sorting is gone into the rubbish mailbox; Drop on and carry out step (2) between the maximin of setting range;
(2) do further go-on-go processing through twit filter module and virus analysis device module, filter in the go-on-go processing procedure at twice, anyly once filter defectively, then mail is judged to be spam, go-on-go is to the rubbish mailbox, and twice filtration is all qualified carries out step (3);
(3) accessing the degree of belief numerical value of corresponding source address and the mean value of setting range maximin again from the degree of belief database compares, mail greater than this mean value is judged to be normal email, mail-sorting is gone into normal mailbox, mail less than this mean value is judged to be spam, and mail-sorting is gone into the rubbish mailbox;
(4) by result to mail treatment, the degree of belief value of source of email address correspondence in the revision degree of belief database, the degree of belief value of address, increase normal email source correspondence, the degree of belief value of address, minimizing spam source correspondence.
5. the method for go-on-go spam according to claim 4 is characterized in that: the step of the degree of belief value of source of email address correspondence also comprises in the revision degree of belief database:
Foundation increases and decreases the degree of belief value of other addresses of items of mail of the current mail of forwarding that obtains to the increase and decrease of the degree of belief value of current source of email address correspondence.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB2006100351554A CN100490392C (en) | 2006-04-19 | 2006-04-19 | A garbage mail processing system and garbage mail sorting method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB2006100351554A CN100490392C (en) | 2006-04-19 | 2006-04-19 | A garbage mail processing system and garbage mail sorting method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101060421A CN101060421A (en) | 2007-10-24 |
| CN100490392C true CN100490392C (en) | 2009-05-20 |
Family
ID=38866328
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CNB2006100351554A Active CN100490392C (en) | 2006-04-19 | 2006-04-19 | A garbage mail processing system and garbage mail sorting method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN100490392C (en) |
Families Citing this family (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2127311B1 (en) | 2007-02-02 | 2013-10-09 | Websense, Inc. | System and method for adding context to prevent data leakage over a computer network |
| CN101150756B (en) * | 2007-11-08 | 2010-05-19 | 电子科技大学 | A spam filtering method |
| US8370948B2 (en) * | 2008-03-19 | 2013-02-05 | Websense, Inc. | System and method for analysis of electronic information dissemination events |
| US9130986B2 (en) | 2008-03-19 | 2015-09-08 | Websense, Inc. | Method and system for protection against information stealing software |
| US9015842B2 (en) | 2008-03-19 | 2015-04-21 | Websense, Inc. | Method and system for protection against information stealing software |
| WO2010038143A1 (en) * | 2008-10-01 | 2010-04-08 | Network Box Corporation Limited | Electronic communication control |
| CN101499981B (en) * | 2009-03-19 | 2014-10-22 | 哈尔滨工程大学 | E-mail gateway type systematic mail account maintaining method |
| US9130972B2 (en) | 2009-05-26 | 2015-09-08 | Websense, Inc. | Systems and methods for efficient detection of fingerprinted data and information |
| CN102098638A (en) * | 2010-12-15 | 2011-06-15 | 成都市华为赛门铁克科技有限公司 | Short message sorting method and device, and terminal |
| US8640245B2 (en) * | 2010-12-24 | 2014-01-28 | Kaspersky Lab, Zao | Optimization of anti-malware processing by automated correction of detection rules |
| US9241259B2 (en) | 2012-11-30 | 2016-01-19 | Websense, Inc. | Method and apparatus for managing the transfer of sensitive information to mobile devices |
| US9558452B2 (en) * | 2013-11-08 | 2017-01-31 | Microsoft Technology Licensing, Llc | Hierarchical statistical model for behavior prediction and classification |
| CN104636381B (en) * | 2013-11-14 | 2018-02-27 | 联想(北京)有限公司 | The processing method and processing device of information |
| WO2015096120A1 (en) * | 2013-12-27 | 2015-07-02 | Intel Corporation | Techniques for implementing a secure mailbox in resource-constrained embedded systems |
| KR102150624B1 (en) * | 2014-07-01 | 2020-09-01 | 삼성전자 주식회사 | Method and apparatus for notifying smishing |
| CN104506356B (en) * | 2014-12-24 | 2018-06-15 | 网易（杭州）网络有限公司 | A kind of method and apparatus of determining IP address credit worthiness |
| US10504029B2 (en) | 2015-06-30 | 2019-12-10 | Microsoft Technology Licensing, Llc | Personalized predictive models |
| CN105610833B (en) * | 2015-12-30 | 2019-01-18 | 新浪网技术(中国)有限公司 | A kind of mail anti-spam method and system based on IP credit value |
| CN109218162B (en) * | 2017-07-05 | 2021-04-27 | 北京二六三企业通信有限公司 | Mail delivery method and device |
| CN109391535B (en) * | 2017-08-02 | 2022-03-04 | 阿里巴巴集团控股有限公司 | Domain-level contact person determining method, and junk mail judging method and device |
| EP3451626B1 (en) * | 2017-08-31 | 2021-11-17 | FIMER S.p.A. | Method and system for data stream processing |
| CN109347807B (en) * | 2018-09-20 | 2021-03-19 | 北京计算机技术及应用研究所 | Trust-based differential intrusion prevention method |
| CN108965350B (en) * | 2018-10-23 | 2021-04-23 | 杭州安恒信息技术股份有限公司 | Mail auditing method, device and computer readable storage medium |
| CN110474837A (en) * | 2019-08-19 | 2019-11-19 | 赛尔网络有限公司 | A kind of Junk mail processing method, device, electronic equipment and storage medium |
| CN113590531B (en) * | 2021-07-26 | 2021-12-31 | 浙江汇鼎华链科技有限公司 | Data classification storage system and method based on big data |
-
2006
- 2006-04-19 CN CNB2006100351554A patent/CN100490392C/en active Active
Non-Patent Citations (2)
| Title |
|---|
| 邮件网关过滤与监控系统研究与实现. 郑晟，全文，昆明理工大学. 2005 |
| 邮件网关过滤与监控系统研究与实现. 郑晟，全文，昆明理工大学. 2005 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101060421A (en) | 2007-10-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN100490392C (en) | A garbage mail processing system and garbage mail sorting method | |
| US7610344B2 (en) | Sender reputations for spam prevention | |
| CN103198123B (en) | For system and method based on user's prestige filtering spam email message | |
| EP1635524A1 (en) | A method and system for identifying and blocking spam email messages at an inspecting point | |
| US7469292B2 (en) | Managing electronic messages using contact information | |
| US8776210B2 (en) | Statistical message classifier | |
| US8363568B2 (en) | Message filtering method | |
| US7660865B2 (en) | Spam filtering with probabilistic secure hashes | |
| US7996471B2 (en) | Electronic message distribution system | |
| KR101143194B1 (en) | Obfuscation of spam filter | |
| US9100335B2 (en) | Processing a message based on a boundary IP address and decay variable | |
| WO2004013796A1 (en) | Practical techniques for reducing unsolicited electronic messages by identifying sender’s addresses | |
| KR20060006769A (en) | Feedback loop for spam prevention | |
| WO2006026263A2 (en) | Controlling transmission of email | |
| CN103634308A (en) | Safety detection method and device for instant messaging tool | |
| CN1863170A (en) | Method for processing junk E-mail and computer readable memory medium | |
| CN102413076A (en) | Spam mail judging system based on behavior analysis | |
| GB2382900A (en) | Regulating receipt of electronic mail with a whitelist based on outgoing email addresses | |
| US20070088789A1 (en) | Method and system for indicating an email sender as spammer | |
| CN105007218A (en) | Junk e-mail resistance method and system thereof | |
| Gansterer et al. | Anti-spam methods-state of the art | |
| CN105635080A (en) | E-mail safety management system and method based on content filtering | |
| US20020147783A1 (en) | Method, device and e-mail server for detecting an undesired e-mail | |
| EP1955504A2 (en) | Anti-spam application storage system | |
| KR100999977B1 (en) | Information drain prevention method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |