Source: http://www.google.com/patents/US20080126344?dq=6,199,048
Timestamp: 2015-01-30 05:10:04
Document Index: 392762290

Matched Legal Cases: ['art 300', 'art 300', 'art 300', 'art 300', 'art 300', 'art 300', 'art 300', 'art 300']

Patent US20080126344 - Hierarchical, traceable, and association reputation assessment of email domains - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsA reputability analysis system receives a domain assessment request associated with a domain and accesses a database to find a match for the domain. A reputability score is derived according to a hierarchical analysis of a matching domain in the database. Traceability, accountability, and association...http://www.google.com/patents/US20080126344?utm_source=gb-gplus-sharePatent US20080126344 - Hierarchical, traceable, and association reputation assessment of email domainsAdvanced Patent SearchPublication numberUS20080126344 A1Publication typeApplicationApplication numberUS 11/945,208Publication dateMay 29, 2008Filing dateNov 26, 2007Priority dateNov 27, 2006Also published asUS7853614Publication number11945208, 945208, US 2008/0126344 A1, US 2008/126344 A1, US 20080126344 A1, US 20080126344A1, US 2008126344 A1, US 2008126344A1, US-A1-20080126344, US-A1-2008126344, US2008/0126344A1, US2008/126344A1, US20080126344 A1, US20080126344A1, US2008126344 A1, US2008126344A1InventorsAuren Hoffman, Jeremy Lizt, Vivek Sodera, Manish ShahOriginal AssigneeRapleaf, Inc.Export CitationBiBTeX, EndNote, RefManReferenced by (8), Classifications (6), Legal Events (3) External Links: USPTO, USPTO Assignment, EspacenetHierarchical, traceable, and association reputation assessment of email domainsUS 20080126344 A1Abstract A reputability analysis system receives a domain assessment request associated with a domain and accesses a database to find a match for the domain. A reputability score is derived according to a hierarchical analysis of a matching domain in the database. Traceability, accountability, and association information associated with the domain assessment request may also be used to adjust the reputability score.
receiving an assessment request associated with a domain; accessing a database to find a match for the domain; deriving a reputability score according to a hierarchical analysis of a matching domain in the database; and sending the reputability score in reply to the assessment request. 2. The method of claim 1, further comprising:
determining whether a first domain level matches the domain in the assessment request; using a first reputability value associated with the first domain level for deriving the reputability score when the first domain level matches the domain; determining whether a second sub-domain level of the first domain level matches the domain; and using a second reputability value associated with the second sub-domain level for deriving the reputability score when the second sub-domain level matches the domain in the assessment request. 3. The method of claim 1, further comprising:
finding a lowest sub-domain level in the database that matches the domain in the assessment request; using a reputability value associated with the lowest matching sub-domain level for deriving the reputability score. 4. The method of claim 1, further comprising providing, in reply to the assessment request, additional information associated with the domain.
identifying traceability or association information associated with the domain in the assessment request; and deriving a reputability score according to the identified traceability and association information. 7. The method according to claim 6 wherein the traceability or association information includes domains used by company employees.
8. The method according to claim 6 wherein the traceability or association information includes domains that require users to provide credit card information or personal identification information.
9. The method according to claim 6 wherein the traceability or association information includes domains that require users to belong to or be associated with an organization associated with the domain.
a hierarchical domain search engine; a database including a reputability score associated with a domain; wherein, in operation, the hierarchical domain search engine, in response to a domain assessment request associated with the domain, analyzes domain hierarchies in the domain database to determine a reputability score associated with the domain, and returns, in reply to the domain assessment request, the reputability score. 11. The system of claim 10 wherein the hierarchical domain search engine determines the reputability score according to a longest matching domain extension level in the database.
13. The system of claim 10, wherein the hierarchical domain search engine adjusts the reputability score according to traceability and association information associated with the domain.
17. The system of claim 10, wherein, in operation, the hierarchical domain search engine provides feedback to the admin system regarding the domain assessment request.
18. A means for assessing reputability of email, comprising:
a database for storing email domains and sub-domains with associated reputability scores; a means for accessing the database to derive a reputability score for:
a domain if a reputability score for a sub-domain of the domain is not found in the database;
the sub-domain if a reputability score for the sub-domain is stored in the database;
a means for providing the reputability score to an email domain assessment means. 19. The means for assessing reputability of email according to claim 18, wherein, the reputability score is adjusted according to traceability, accountability, and association information associated with the domain.
20. The means for assessing reputability of email according to claim 18, wherein, if the reputability score is for the sub-domain, the sub-domain is a highest hierarchical sub-domain of the domain for which a reputability score is stored in the database.
21. The means for assessing reputability of email according to claim 18, wherein the email domain assessment means is associated with one of the group consisting of: a wiki, a blog, a forum, a web page, a social network, a community web site, an email client, an e-commerce site.
22. The means for assessing reputability of email according to claim 18, further comprising, a means for providing feedback regarding domains and sub-domains that are queried against the database.
23. The means for assessing reputability of email according to claim 18, further comprising, a means for providing additional information associated with the domain, if a reputability score for a sub-domain is not found in the database, or the sub-domain, if the sub-domain is stored in the database. Description
BACKGROUND When receiving an email from an unknown sender, the reputability of the email address vis-�-vis the sender can be unclear. Email may be checked against a contacts list, spam whitelist, or spam blacklist. However, these techniques do not assess the characteristics of the email domains.
Any website that accepts content submissions from the public (e.g. blogging sites, social networking sites, publication sites, wikis, etc.) has to find a balance between keeping the site accessible to encourage submissions, and protecting against fraudulent or vandalizing behavior. One example of vandalism is the widespread issue of �wikibots�, computer programs that post unwanted and often irrelevant advertising on generally accessible wiki pages.
Some domain registry systems may assign reputation values to different registered internet domains based on user feedback or some computational algorithm. These registry systems only provide reputation information for internet domains registered by that particular registry service. Even the registered domains will not have reputation information unless the registry service receives feedback or data input identifying previous actions associated with the registered domains. When domain feedback or data input is available, the registry service then automatically generates reputation values that correspond with the feedback information. Thus, current domain reputation assignment systems only cover certain internet domains. For example, while a domain registry system may assign a reputation on a .com domain, it cannot compare a .edu or a .gov (or potentially a cn) domain with a .com
Domain hierarchical reputation assessment uses email addresses and knowledge of email domains and how email addresses are distributed within those domains in order to generate a �reputation� or likelihood of good behavior. Email addresses or email address domains are submitted to a system that returns a score representing the �reputability� or �verity� of the email address. The reputability score is determined by checking a database to see if it contains a reputability score for the given domain. Even if there is no listing for that domain, the system will derive a reputability score based on hierarchical analysis of the domain and/or based on the traceability, accountability, or association of the domain users.
Domain Hierarchy One example of the email domain database 104 is shown in FIG. 2 and includes data associated with different email addresses, in particular different email domains 140. The email domains 140 are structured hierarchically, and have associated reputability scores at different hierarchical levels. The domains 140 while shown hierarchically in FIG. 2 may actually be stored in any of a variety of different ways where different portions of the same domain are linked together.
One particular domain 140A has a level-1/main/master domain 142A with an associated reputability score 142B. The level-1 main domain for example may be extensions such as �.com�, �.gov�, �.mil�, �.edu�, �.de�, or any other domain entity or domain country used for communicating over the internet. Any number of these hierarchical domains 140A-140N may exist in database 104. The reputability score 142B is shown as a letter A but represents a number.
FIG. 3 shows one specific example of an email address domain �someone@may.be.reputable.com� that may be stored in database 104. The master domain �.com� may have an associated reputability score that is relatively uninformative because there are many email addresses that end in �.com� that are not reputable, and many that are reputable. In the email domain database 104, the domain �reputable.com� may have an associated reputability score that is more informative than �.com,� but less informative than the sub-domain �be.reputable.com.�
Assume that the email domain database 104 does not have the record for �may.be.reputable.com.� In this example, �be.reputable.com� may provide the greatest amount of information because it is highest in the domain hierarchy. It should be noted that �be.reputable.com� and �reputable.com� could provide equal amounts of information (e.g., the reputability scores could be the same), but it is unlikely that �reputable.com� would provide more information than �be.reputable.com.�
Referring both to FIG. 1 and FIG. 3, the client 106 presumably wishes to make use of the data in the email domain database 104 to assess the reputability of �someone@may.be.reputable.com�. Accordingly, the client 106 sends a domain assessment request 120 to the server 108. The server 108 uses the hierarchical/traceability email domain search engine 110 to access the email domain database 104. In alternative embodiments, one or more of the admin 102, the email domain database 104, and the client 106 could be logically or physically included in or local with respect to the server 108.
The hierarchical email domain search engine 110 logically checks the highest hierarchical level for a match. The highest hierarchical level in database 104 for �someone@may.be.reputable.com� is �may.be.reputable.com,� If there was no match for �may.be.reputable.com.�, the hierarchical email domain search engine 110 would check �be.reputable.com� for a match, then �reputable.com�, and finally, �.com�.
A value associated with the highest match is returned as the reputability score. Assume for the purpose of example that �be.reputable.com,� �reputable.com,� and �.com� have reputability scores of 60, 55, and 50, respectively. Since in this example, �be.reputable.com� is the highest match in the domain hierarchy, a value of 60 is sent from the server 108 to the client 106 as reputability score 122.
Advantageously, the system 100 can facilitate assessment of reputability or verity of the domain of an email addresses, as described above. In a non-limiting embodiment, the reputability of the domain can, in turn, be used to assess the reputability of the actual email address. For example, in FIG. 3, a manager could determine that �someone@may.be.reputable.com� is deserving of a reputability score that is different from that of �may.be.reputable.com.� In such an embodiment, it may be desirable to include in database 104, or include in another database 180, the reputability scores for particular email addresses 182 and 184. The email address database 180 may or may not be logically or physically included in the email domain database 104.
The flowchart 300 continues to module 304 where an email domain database is accessed for a highest domain hierarchy. The highest domain of an email address is typically everything after the �@� character. However, in an embodiment that includes providing reputability information for a specific email address (e.g., Jeremy@companyA.com), the highest �domain� could be considered the entire email address itself. Notably, an email address, strictly speaking, is not a �domain,� but the applicability of this technique should be nevertheless apparent.
In the example of FIG. 4, the flowchart 300 continues to decision point 306 where it is determined whether a reputability score is available for the highest �domain.� If it is determined that a reputability score is available for the �domain� (306-Y), the flowchart 300 continues to module 308 where the reputability score is sent in response to the domain assessment request. Additional information may be sent with (or, in an alternative embodiment, instead of) the reputability score 122, such as text identifying the owner of the email address or domain, or text characterizing the email address or domain.
If it is determined that a reputability score is not available for the �domain� (306-N), the flowchart 300 continues to module 310 where it is determined whether a next higher �domain� is available. In an embodiment where an email address is treated as the highest �domain,� the next higher domain will be, in a typical implementation, the value after @. In an embodiment where the highest domain is the actual domain, the next higher domain will be the value after the first dot (.) following @. In any case, at each subsequent iteration, a next domain or super-domain is considered. Each domain level may be differentiated by the period �.� separating each domain extension or sub-domain. A domain need not appear in quotes to cover the embodiment wherein an email address is treated as the highest level �domain�.
If it is determined that a next higher domain is available (310-Y), then the flowchart 300 continues to module 312 where the next higher domain is considered. The flowchart 300 then loops back to decision point 306 where it is determined whether a reputability score is available for the next higher domain, and the flowchart 300 continues as described previously. If, on the other hand, it is determined that a next higher domain is not available (310-N), then the flowchart 300 continues to module 314 where �no match� is sent in reply to the domain assessment request 120. This means that no reputability score is available for the domain. However, there may be other information that is sent. For example, text associated with the owner of the email address or domain, or some other information. Also, a reputability score 122 may be sent based on traceability or association information as described in more detail below.
Traceability/Association Consider the email address �jeremy@companyA.com,� which denotes that the owner of this address is an employee of or somehow associated with company A. As with this email address, every domain is going to have certain properties, and will distribute email addresses in a particular way, thus there is no global generalization that can be made for all email address domains. Advantageously, the email domain database 104 facilitates cataloging the properties of each domain name entry, specifically regarding how email addresses of that domain are assigned reputability scores.
Take for example, an email address with the domain �harvard.edu�. This domain indicates that its owner is probably a student, alumni, contractor, or employee of Harvard University. The �edu� domain is associated with educational institutions that are required to satisfy different criteria before using the �edu� domain. More stringent qualifications are generally associated with the �edu� domain than required for the �com� domain. Therefore, domains under �edu� may be assigned higher reputability scores than domains under the �com� domain.
Further, any user registering an email address under �harvard.edu� may be required to go through a more rigorous and traceable registration process than other �com� email registrations. For example, a user using the email address �billjohnson@alum.harvard.edu� may be required to be an alumni of Harvard University. Accordingly, the user would likely be traceable through the alumni records at Harvard University and have a higher reputation for being associated with Harvard University.
Further, the user of �billjohnson@alum.harvard.edu� may have more accountability than users of other email addresses. For example, if the user conducts illicit or unacceptable behavior using the email address �billjohnson@alum.harvard.edu�, then not only would the email address be subject to removal by the university but the user could also be subject to discipline or removal from the university alumni association. Thus, this email address may be assigned a relatively high reputability score since the actual identify of the user with this email domain is highly traceable and identifiable and user accountability is relatively high.
Similarly, an email address with the domain �google.com� may indicate that its owner is an employee of Google. Thus, the user of the email address �jillsmith@google.com� is likely to be traceable through Google employee records and accountable to Google management for certain activities related to the email address. In this example, internet addresses using the �google.com� domain may be assigned a relatively high reputability score (based on the traceability aspect as well as the association component).
Conversely, an email address with the domain �gmail.com� indicates very little and only shows that its owner registered for a free email account at Google's GMail web service. It could be easy for vandals or spammers to use readily available email addresses, such as a gmail.com address or an address from an unknown domain, that they can use a few times and then never use again. If used carefully, these email addresses are difficult to trace back to a real, human identity.
The server 108 in operation 354 determines if other sub-domains or extensions exist for the email address that may provide additional traceability or association information. For example, an email address �billjones@staff.chemistrydepartment.stateuniversity.edu� may be more traceable to a particular human-being than the email address �bill@stateuniversity.edu� and also have a much more specific association. Accordingly, the additional information provided in the first email address may be associated with a higher traceability and association than the second email address. The server 108 continues to parse through the email address until no further traceability information can be identified.
Referring to FIGS. 1, 2, and 5, the email domain database 104 may include additional traceability, and association information 136 about a domain. For example, the email domain database 104A may include a description 136 associated with �companyA.com� that �email addresses in this domain are used exclusively by company A employees.� This traceability and association information 136 could be provided to the client 106 in addition to or instead of a reputability score 122. The accountability and association information 136 could be in the form of a text description or could be supplied in the form of a traceability/association score. The domain search engine 110 may use traceability/association information 136 to automatically generate a traceability/association score or use the information 136 to adjust or weight a previously determined reputability score 122.
In this way, the client 106, when querying �jeremy@companyA.com� would know, for example, that �jeremy@companyA.com� is likely to be owned by a company A employee in contrast to �joe@yahoo.com�, which is likely not owned by a Yahoo! employee. Emails �@yahoo.com� are part of a free web-based email service offered by Yahoo! to the general public. Most Yahoo employees in the U.S. have an official work email address ending in �yahoo-inc.com�. Thus, this employee domain traceability/association information 136 notifies the server 108 of another aspect of domain reputability.
In another non-limiting embodiment, public users could post information 134 about a particular email domain 140A that might be relevant to another user that uses the system to look up an email address. For example, a user might post information 134 about �companyA.com� indicating �Email addresses in this domain are used exclusively by company A employees and contractors.� In this case, the system 100 in FIG. 1 may be self-referencing in order to allow only those public users with a high enough reputability score to post information about other domains, email addresses, or entities, if applicable.
Filtering The client 106 in FIG. 1 uses the domain filtering engine 112 to determine whether the reputability score 122 is adequate for a particular purpose. For example, if the client 106 includes a spam filter 124, the spam filter may be set to delete emails that have a reputability score of less than, for example, 30. Those emails that are included in a spam whitelist may be excluded from the filtering and emails that are included in a spam blacklist may be included in the filtering. The emails with a reputability score of less than 80 are sent to a spam folder.
The computer 502 interfaces to external systems through the communications interface 510, which may include a modem or network interface. The communications interface 510 can be considered to be part of the computer system 500 or a part of the computer 502. The communications interface 510 can be an analog modem, ISDN modem, DSL modem, cable modem, token ring interface, satellite transmission interface (e.g. �direct PC�), or other interfaces for coupling a computer system to other computer systems. Although conventional computers typically include a communications interface of some type, it is possible to create a computer that does not include one, thereby making the communications interface 510 optional in the strictest sense of the word.
The processor 508 may include, by way of example but not limitation, a conventional microprocessor such as an Intel Pentium microprocessor or Motorola power PC microprocessor. While the processor 508 is a critical component of all conventional computers, any applicable known or convenient processor could be used for the purposes of implementing the techniques described herein. The memory 512 is coupled to the processor 508 by a bus 520. The memory 512, which may be referred to as �primary memory,� can include Dynamic Random Access Memory (DRAM) and can also include Static RAM (SRAM). The bus 520 couples the processor 508 to the memory 512, and also to the non-volatile storage 516, to the display controller 514, and to the I/O controller 518.
The non-volatile storage 516, which may be referred to as �secondary memory,� is often a magnetic hard disk, an optical disk, or another form of storage for large amounts of data. Some of this data is often written, by a direct memory access process, into memory 512 during execution of software in the computer 502. The non-volatile storage 516 may include a block-based media device. The terms �machine-readable medium� or �computer-readable medium� include any known or convenient storage device that is accessible by the processor 508 and also encompasses a carrier wave that encodes a data signal.
The computer system 500 may be controlled by an operating system (OS). An OS is a software program-used on most, but not all, computer systems�that manages the hardware and software resources of a computer. Typically, the OS performs basic tasks such as controlling and allocating memory, prioritizing system requests, controlling input and output devices, facilitating networking, and managing files. Examples of operating systems for personal computers include Microsoft Windows�, Linux, and Mac OS�. Delineating between the OS and application software is sometimes rather difficult. Fortunately, delineation is not necessary to understand the techniques described herein, since any reasonable delineation should suffice.
As used herein, algorithmic descriptions and svmbolic representations of operations on data bits within a computer memory are believed to most effectively convey the techniques to others skilled in the art. An algorithm is here, and generally, conceived to be a self-consistent sequence of operations leading to a desired result. The operations are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like.
Referenced byCiting PatentFiling datePublication dateApplicantTitleUS8370902Jan 29, 2010Feb 5, 2013Microsoft CorporationRescuing trusted nodes from filtering of untrusted network entitiesUS8621005Apr 28, 2011Dec 31, 2013Ttb Technologies, LlcComputer-based methods and systems for arranging meetings between users and methods and systems for verifying background information of usersUS8799295 *Apr 3, 2009Aug 5, 2014Network Solutions Inc.Method and system for scoring domain namesUS8818882 *Jul 29, 2010Aug 26, 2014Visa International Service AssociationAlias identity and reputation validation engineUS20110047040 *Jul 29, 2010Feb 24, 2011Mark CarlsonAlias identity and reputation validation engineUS20110138298 *Dec 8, 2009Jun 9, 2011Joseph Anderson AlfredMethod and apparatus for providing control of social networking sitesUS20110196927 *Feb 2, 2011Aug 11, 2011Richard Allen VanceSocial Networking Application Using Posts to Determine CompatibilityWO2011028363A2 *Aug 6, 2010Mar 10, 2011Visa International Service AssociationAlias identity and reputation validation engine* Cited by examinerClassifications U.S. Classification1/1, 707/E17.014, 707/999.005International ClassificationG06F17/30Cooperative ClassificationG06Q10/107European ClassificationG06Q10/107Legal EventsDateCodeEventDescriptionMay 14, 2014FPAYFee paymentYear of fee payment: 4Jul 29, 2013ASAssignmentOwner name: LIVERAMP, INC., CALIFORNIAEffective date: 20130723Free format text: CHANGE OF NAME;ASSIGNOR:RAPLEAF, INC.;REEL/FRAME:030954/0970Dec 7, 2007ASAssignmentOwner name: RAPLEAF, INC., CALIFORNIAFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:HOFFMAN, AUREN;LIZT, JEREMY;SODERA, VIVEK;AND OTHERS;REEL/FRAME:020215/0512Effective date: 20071126RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services