US 7,953,814 B1Grant
Stopping and remediating outbound messaging abuse
Issue Date:2011-05-31
•19 Claims
•23 Drawing Sheets
Abstract
Systems and methods are provided for allowing subscriber message sending profiles to be maintained and used in conjunction with behavior-based anomaly detection techniques and traditional content-based spam signature filtering to enable application of appropriate message disposition policies to outbound subscriber message traffic. According to one embodiment, subscriber profiles are constructed for multiple subscriber accounts associated with a service provider based on outbound message flow originated from the subscriber accounts. Then, possible subscriber account misuse may be discovered by performing behavior-based anomaly detection, including a comparison of a subscriber profile associated with the subscriber account with recent subscriber account usage information, to identify one or more behavioral anomalies in outbound message flow originated from a subscriber account, the behavior-based anomaly detection.
Metadata
Assignee
- McAfee, Inc.
Inventors
- C. Scott Chasin
- Wei Lin
- Paul Kincaid-Smith
Application Information
Application Number:US 11/365,130
Filing Date:2006-02-28
Priority Date:2005-02-28
Art Unit:2614
Classifications
IPC:
G06F15/16G06F11/00
Patent Drawings (23 sheets)
Description
Cross-Reference to Related Applications
[0001] This application claims the benefit of U.S. Provisional Application No. 60/657,038, filed on Feb. 28, 2005, which is hereby incorporated by reference for all purposes.
Copyright Notice
[0002] Contained herein is material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction of the patent disclosure by any person as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights to the copyright whatsoever. Copyright © 2005-2006 MX Logic, Inc.
Background
[0003] 1. Field
[0004] Embodiments of the present invention generally relate to systems and methods for remediating outbound messaging abuse. More specifically, embodiments of the present invention provide for systems and methods of allowing service providers filter outbound subscriber email traffic for spam and/or worm-oriented messages using one or more of individual subscriber email sending reputation, real-time analysis of message content and behavior-based anomaly detection.
[0005] 2. Description of Related Art
[0006] Reputation has become a new frontier in spam fighting and many different companies have introduced reputation databases that provide insight into the historical email sending behavior of Internet Protocol (IP) addresses or email servers. These new email reputation services also are beginning to provide accreditation services, where email sending organizations that have no email sending history can pay to have one of these services vouch for them, presumably after a fair amount of due diligence has been done by the accrediting service.
[0007] Using reputation on the Internet to infer future behavior or to determine access to services is relatively new. However, there have been some implementations, such as EBay's seller reputation or Amazon's rating system for reviewers that have worked fairly well in minimizing participation risk. But, unlike the EBay and Amazon models, the email reputation schemes that have been introduced to the market build their reputation not from individuals, but rather from organizational identifiers, such as IP addresses or domain names.
[0008] There are problems with using IP addresses to track email sending behavior. For example, it is fairly common for a message to travel multiple hops before arriving at a recipient's email gateway, thus making it difficult to always identify the true IP address of the originating sender. In fact, as it turns out, those that would be most likely to hide their email sending identity or originating IP address, often will purposely route their messages through several unauthorized gateways.
[0009] Meanwhile, because the email protocol does not provide for authentication, domain name reputation for email sending has not had an opportunity to be successful. However, the industry anticipates adopting a protocol extension that will remove fraudulent email envelopes and provide reputation services with a static identity for organizations in which email sending behavior can be associated.
[0010] Since IP addresses and domain names are usually tied to organizations, they are often shared by all the end-users within those organizations. Most Internet service providers use dynamic IP addresses for their subscribers, which provide a new IP address with each Internet session. Other service providers and enterprises force their end users to send their messages through authenticated email gateways that have their own shared IP addresses. The lack of persistent identity with IP addresses poses a real risk for email sending reputation, which will mostly be based on transient user behavior.
[0011] For organizations with small groups of email senders it is probably okay for their reputation to be tied to a domain name; however, for larger businesses and service providers, this creates an enormous challenge as the organizational reputation is constructed from the aggregate of each individual user's behavior. In some instances, millions of independent end users are responsible for an organization's email sending behavior. Worse yet, an end user's identity can be hijacked by a spam sending virus, thereby compounding the trust problem.
Summary
[0012] Systems and methods are described for allowing subscriber message sending profiles to be maintained and used in conjunction with behavior-based anomaly detection techniques and traditional content-based spam signature filtering to enable application of appropriate message disposition policies to outbound subscriber message traffic. According to one embodiment, subscriber profiles are constructed for multiple subscriber accounts associated with a service provider based on outbound message flow originated from the subscriber accounts. Then, possible subscriber account misuse may be discovered by performing behavior-based anomaly detection, including a comparison of a subscriber profile associated with the subscriber account with recent subscriber account usage information, to identify one or more behavioral anomalies in outbound message flow originated from a subscriber account, the behavior-based anomaly detection.
[0013] A more complete understanding of various embodiments and features of the present invention may be derived by referring to the detailed description of preferred embodiments and claims when considered in connection with the figures.
Brief Description of the Drawings
[0014] In the Figures, similar components and/or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label with a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.
[0015] FIG. 1 conceptually illustrates a real-time attack recognition architecture according to one embodiment of the present invention.
[0016] FIG. 2 is a simplified high level architectural view of a service provider network employing sender reputation management functionality in accordance with one embodiment of the present invention.
[0017] FIG. 3 illustrates interactions among various functional units of a sender reputation gateway according to one embodiment of the present invention.
[0018] FIG. 4 illustrates an example of a computer system with which embodiments of the present invention may be utilized.
[0019] FIG. 5 is a flow diagram illustrating outbound subscriber traffic processing in accordance with one embodiment of the present invention.
[0020] FIG. 6 is a flow diagram illustrating behavior-based anomaly detection processing in accordance with one embodiment of the present invention.
[0021] FIGS. 7A-B depict various exemplary overview user interface (UI) screen shots in accordance with one embodiment of the present invention.
[0022] FIGS. 8A-E depict various exemplary configuration UI screen shots in accordance with one embodiment of the present invention.
[0023] FIGS. 9A-F depict various exemplary policies UI screen shots in accordance with one embodiment of the present invention.
[0024] FIGS. 10A-C depict various exemplary reporting UI screen shots in accordance with one embodiment of the present invention.
Detailed Description
[0025] Systems and methods are described for allowing subscriber message sending profiles to be maintained and used in conjunction with behavior-based anomaly detection techniques and traditional content-based spam signature filtering to enable application of appropriate message disposition policies to outbound subscriber message traffic. According to one embodiment, a sender reputation gateway (SRG) may be employed by an organization, such as an Internet service provider (ISP), service provider or other company, to police email sending conduct of their subscribers and thereby protect their organizational email sending reputation.
[0026] In one embodiment, the SRG models individual subscriber accounts and detects deviations from this model in outbound message flow to identify potential misuse of subscriber accounts. For example, the SRG may build subscriber profiles for each subscriber based on behavior data extracted from each email message originated by the subscriber. A reputation score or other measure of subscriber trustworthiness may then be based upon short-term and/or long-term reputation data. Such subscriber reputation data may be used to determine an immediate email action for a current email message in question and/or a long-term subscriber action for all subsequent email messages originated by the particular subscriber. In one embodiment, reputation data generated from a single email message may be used to determine message disposition, e.g., deny, add blind carbon copy (bcc) recipient, etc., for that message itself. According to other embodiments, reputation data generated from a single email message can be combined with long-term reputation data to determine if actions need to be taken against the subscriber, such as redirect to relay pool, reduce the subscriber's privileges or lower the subscriber's trustworthiness rating.
[0027] The SRG may perform multiple content filters on outbound subscriber traffic. In addition to the reputation filter, the content filters may include one or more of a spam filter, a virus filter, a phishing filter and a throttle filter. In one embodiment, the SRG also provides web-based access to network operations analysts to message disposition policies, notifications, alerts, submission status and traffic reports.
[0028] In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. It will be apparent, however, to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
[0029] Embodiments of the present invention may be provided as a computer program product which may include a machine-readable medium having stored thereon instructions which may be used to program a computer (or other electronic devices) to perform a process. The machine-readable medium may include, but is not limited to, floppy diskettes, optical disks, compact disc read-only memories (CD-ROMs), and magneto-optical disks, ROMs, random access memories (RAMs), erasable programmable read-only memories (EPROMs), electrically erasable programmable read-only memories (EEPROMs), magnetic or optical cards, flash memory, or other type of media/machine-readable medium suitable for storing electronic instructions. Moreover, embodiments of the present invention may also be downloaded as a computer program product, wherein the program may be transferred from a remote computer to a requesting computer by way of data signals embodied in a carrier wave or other propagation medium via a communication link (e.g., a modem or network connection).
[0030] While, for convenience, various embodiments of the present invention may be described with reference to outbound email message abuse, the present invention is equally applicable to various other forms of asynchronous outbound messages, such as instant messages, mobile messages (e.g., SMS, MMS), voice mail and the like.
[0031] For the sake of illustration, various embodiments of the present invention are described herein in the context of computer programs, physical components, and logical interactions within modem computer networks. Importantly, while these embodiments describe various aspects of the invention in relation to modem computer networks and programs, the method and apparatus described herein are equally applicable to other systems, devices, and networks as one skilled in the art will appreciate. As such, the illustrated applications of the embodiments of the present invention are not meant to be limiting, but instead exemplary. Other systems, devices, and networks to which embodiments of the present invention are applicable include, but are not limited to, cellular phones, personal digital assistants (PDAs), pagers, BlackBerry® devices and the like.
Terminology
[0032] Brief definitions of terms, abbreviations, and phrases used throughout this application are given below.
[0033] The terms “connected” or “coupled” and related terms are used in an operational sense and are not necessarily limited to a direct physical connection or coupling. Thus, for example, two devices may be couple directly, or via one or more intermediary media or devices. As another example, devices may be coupled in such a way that information can be passed therebetween, while not sharing any physical connection on with another. Based on the disclosure provided herein, one of ordinary skill in the art will appreciate a variety of ways in which connection or coupling exists in accordance with the aforementioned definition.
[0034] The phrases “in one embodiment,” “according to one embodiment,” and the like generally mean the particular feature, structure, or characteristic following the phrase is included in at least one embodiment of the present invention, and may be included in more than one embodiment of the present invention. Importantly, such phases do not necessarily refer to the same embodiment.
[0035] The phrase “Internet service provider” or “ISP” generally refers to a service provider or other organization that provides access to the Internet. ISPs may provide service via modem, ISDN, cable, DSL or the like and may also offer private line hookups (e.g., T1, fractional T1, etc.). As used herein, the term ISP is intended to encompass online services, such as America Online and CompuServe, that provide members with Internet access as well as members only content, forums and services. While ISPs are typically fee-based companies that provide third party subscribers or members with “dial-up” or direct access to the Internet via SLP, PPP, or TCP/IP, as used herein the term ISP is also intended to encompass companies in their role as employers supplying Internet access to employees and/or contractors. Therefore, for purposes of this application, an enterprise supplying email accounts to its employees acts as an ISP and the employees would be considered subscribers of the ISP.
[0036] If the specification states a component or feature “may”, “can”, “could”, or “might” be included or have a characteristic, that particular component or feature is not required to be included or have the characteristic.
[0037] The term “responsive” includes completely or partially responsive.
[0038] The phrase “service provider” generally refers to a company that provides users with services and/or subscriptions to a messaging network, such as the Internet, a wireless network, a mobile phone network and/or the like. As used herein, the phrase “service provider” is intended to encompass not only companies, such as ISPs, wireless operators, carriers and the like, that may provide access to messaging networks for a fee, but additionally is intended to encompass companies acting in their capacities as employers providing their employees and/or contractors with access to messaging networks. Consequently, for purposes of this application, an enterprise supplying email, voice, voice mail, mobile phone, text messaging and/or other messaging services to its employees and/or contractors acts as a service provider with respect to such employees and/or contractors and such employees and/or contractors would be considered subscribers of the service provider.
[0039] The term “subscriber” generally refers to an individual or company that is a user of services provided by a service provider. For purposes of clarity, in addition to covering the traditional notion of a subscriber as an individual or company that pays a fee for use and/or access to services provided by the service provider, as used herein, the term subscriber is intended to encompass employees, consultants, contractors and/or the like that are provided with services (e.g., email, voice, voice mail, mobile phone, wireless, text messaging and/or other messaging accounts) by virtue of their relationship with an employer or company.
[0040] FIG. 1 conceptually illustrates a real-time attack recognition architecture 130 according to one embodiment of the present invention. In the example depicted, based upon subscriber profile data 120 and SMTP data 110 resulting from subscriber activity 105, the real-time attack recognition architecture 130 (i) applies appropriate message disposition policies 140 to outbound message traffic, (ii) alerts a network operations analyst 145 (e.g., a service provider administrator, network operations center or abuse staff) of potential subscriber account misuse, and (iii) builds and modifies subscriber reputation 150. According to one embodiment, subscriber reputation 150 may be additionally influenced by factors, data and/or internal or external inputs other than SMTP data 110. For example, the subscriber's computer may communicate information to the service provider regarding the presence or absence of certain software. The presence of anti-virus or personal security software installed on a subscriber's computer may positively affect subscriber reputation 150 and the absence of such software may negatively affect subscriber reputation 150. Further, the version of the anti-virus or personal security software installed on the subscriber's computer, whether updates are enabled, and other factors may be taken into consideration when determining subscriber reputation 150.
[0041] Traditional filtering technologies sometimes do not catch new, emerging threats fast enough for effective outbound abuse containment. In one embodiment, the real-time attack recognition engine 130 includes both a spam detection process 131 and a predictive detection model 133 thereby allowing subscriber reputation to be constructed, modified and/or weighted by a model evaluation process 132 based on both content-based spam filtering approaches (e.g., signature and/or statistical spam detection) and behavior-based anomaly detection techniques, described further below, which, in general, seek to identify changes in a sender's observed SMTP behavior to influence the sender's reputation score.
[0042] According to the present example, a data mining process 115 maintains subscriber profile data 120 by tracking, aggregating and applying statistical analysis to various subscriber behavior attributes extracted from SMTP data 110. For example, in one embodiment, subscriber profile data 120 may include, but is not limited to, metrics regarding one or more of:
-
- [0043] the total number of messages originated by the subscriber;
- [0044] the total number of messages originated by the subscriber suspected of being spam;
- [0045] the total number of messages originated by the subscriber suspected of containing a virus;
- [0046] the average number of messages originated by the subscriber;
- [0047] the average number of messages originated by the subscriber within a predefined time interval;
- [0048] the average size of messages originated by the subscriber;
- [0049] the largest size message originated by the subscriber;
- [0050] the maximum size permitted to be originated by the subscriber;
- [0051] the average number of recipients to which messages originated by the subscriber are addressed;
- [0052] the largest number of recipients on a particular message originated by the subscriber;
- [0053] the maximum number of recipients permitted to be addressed by the subscriber on an outbound message;
- [0054] the frequency of recipients;
- [0055] the address format (e.g., pretty name) employed;
- [0056] the average number of message header lines in messages originated by the subscriber;
- [0057] the maximum number of message header lines in messages originated by the subscriber;
- [0058] the average Bayesian spam filter probability score for messages originated by the subscriber;
- [0059] the number of messages originated by the subscriber with attachments;
- [0060] the number of messages originated by the subscriber with attachments of certain types or groups of types (e.g., .exe, .com, .sys, .dll, .scr, .cpl, .api, .drv, .bpl, .zip, etc.);
- [0061] the number of messages originated by the subscriber via a particular mailer;
- [0062] the number of messages originated by the subscriber that include content from a particular character set; and
- [0063] standard deviations relating to the foregoing.
Such metrics may be maintained in aggregate, used to determine time of day patters patterns and/or may be subtotaled by particular time intervals (e.g., previous week, hour or five minute interval; current week, hour or five minute interval). Advantageously, by identifying changes in a user's sending behavior, the real-time attack recognition engine 130 may detect abuse faster than traditional filters. This will result in more effective abuse containment, leading to better outbound reputation scores for the service provider's outbound MTAs, resulting in less frequent blacklisting and thus better quality of service through better email deliverability.
[0064] According to one embodiment, there are two contexts in which reputation scores may be used: to identify an immediate email action and to establish long-term subscriber actions. With respect to immediate email action, reputation data generated from a single email can be used to determine what action (deny, bcc, etc.) to take on the single email itself. Reputation data generated from a single email can be combined with long-term reputation data (e.g., subscriber profiles) to determine if long-term subscriber actions need to be taken against the subscriber (such as redirection to relay pool or whether subscriber privileges are reduced). In implementing long-term subscriber actions, an analogy can be made to someone who bounces a check. The check itself will have a specific action taken on it, but the action taken on the check writer will be affected by whether this is his/her first bad check or whether the writer has a history of bad checks.
[0065] According to one embodiment, reputation-based routing may be performed by the SRG. For example, email messages originated by a subscriber having below a predetermined threshold reputation score may be routed to a transient mail server or dirty pool of IP addresses to protect the service providers' outbound mail server reputation.
[0066] FIG. 2 is a simplified high level architectural view of a service provider network 200 employing sender reputation management functionality in accordance with one embodiment of the present invention. Traditionally, the service provider's outbound delivery pool, e.g., service provider outbound MTA pool 235, interfaces directly with subscribers 225a-225n to deliver outbound message traffic originated by the subscribers 225a-225n to their intended destinations via the Internet 240. According to the present example, a sender reputation gateway (SRG) 205 is logically positioned in front of service provider outbound MTA pool 235 and acts as a proxy for the service provider outbound MTA pool 235 by servicing and responding to SMTP requests directed to the service provider outbound MTA pool 235 issued by subscribers 225a-225n.
[0067] As described further below, SRG 205 may extract behavior attributes, such as those identified above, from outbound message traffic originated by authenticated users and continuously update and store reputation and message sending behavior profiles within a reputation and behavior database 220 for each subscriber 225a-225n based upon the extracted behavior attributes. According to one embodiment, when the reputation and message sending behavior data for a particular subscriber is sufficient to identify behavioral anomalies within a desired confidence interval, the SRG 205 may use the subscriber message sending behavior profile in addition to or instead of message content to filter outbound messages.
[0068] According to one embodiment, the SRG 205 interacts with a connection authentication server 230, such as a Remote Authentication Dial-In User Service (RADIUS) server, and a subscriber database 215 to correlate messaging abuse history with true subscriber identity (obtained via IP address, SMTP AUTH ID, RADIUS ID, web site login ID, Instant Messaging ID, MIN (telephone number) or other means).
[0069] In the embodiment depicted, an SRG control console 210 is a web-based graphical user interface using HTTP or HTTPS protocols. The SRG control console 210 may provide multiple levels of security, accessibility, configuration entities and user roles. According to one embodiment, the SRG control console 210 is the primary interface used by administrators to configure, view and maintain message policies, traffic, system configurations and user access. In one embodiment, the SRG user interface and menu choices are role driven, thereby limiting accessibility to information and data to those user roles permitted to view and/or modify same. As described further below, the SRG control console 210 may also provide various reports to administrators of the service provider network, such as those detailing information about email traffic, filtering, policies, and system usage. As described further below, in one embodiment, depending upon the particular message content filtering configuration, which may be specified via the SRG control console 210, the SRG 205 may apply various anti-virus engines and/or spam filters to outbound message traffic.
Exemplary Computer System Overview
[0070] Embodiments of the present invention include various steps, which will be described in more detail below. A variety of these steps may be performed by hardware components or may be embodied in machine-executable instructions, which may be used to cause a general-purpose or special-purpose processor programmed with the instructions to perform the steps. Alternatively, the steps may be performed by a combination of hardware, software, and/or firmware. As such, FIG. 4 is an example of a computer system 400, such as a workstation, personal computer, client, server or gateway, upon which or with which embodiments of the present invention may be utilized.
[0071] According to the present example, the computer system includes a bus 401, at least one processor 402, at least one communication port 403, a main memory 404, a removable storage media 405 a read only memory 406, and a mass storage 407.
[0072] Processor(s) 402 can be any known processor, such as, but not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), or Motorola® lines of processors. Communication port(s) 403 can be any of an RS-232 port for use with a modem based dialup connection, a 10/100 Ethernet port, or a Gigabit port using copper or fiber. Communication port(s) 403 may be chosen depending on a network such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system 400 connects.
[0073] Main memory 404 can be Random Access Memory (RAM), or any other dynamic storage device(s) commonly known in the art. Read only memory 406 can be any static storage device(s) such as Programmable Read Only Memory (PROM) chips for storing static information such as instructions for processor 402.
[0074] Mass storage 407 can be used to store information and instructions. For example, hard disks such as the Adaptec® family of SCSI drives, an optical disc, an array of disks such as RAID, such as the Adaptec family of RAID drives, or any other mass storage devices may be used.
[0075] Bus 401 communicatively couples processor(s) 402 with the other memory, storage and communication blocks. Bus 401 can be a PCI/PCI-X or SCSI based system bus depending on the storage devices used.
Removable storage media 405 can be any kind of external hard-drives, floppy drives, IOMEGA® Zip Drives, Compact Disc-Read Only Memory (CD-ROM), Compact Disc-Re-Writable (CD-RW), Digital Video Disk-Read Only Memory (DVD-ROM).
[0076] The components described above are meant to exemplify some types of possibilities. In no way should the aforementioned examples limit the scope of the invention, as they are only exemplary embodiments.
[0077] In conclusion, embodiments of the present invention provide novel systems and methods for allowing subscriber message sending profiles to be maintained and used in conjunction with behavior-based anomaly detection techniques and traditional content-based filtering to enable application of appropriate message disposition policies to outbound subscriber traffic. While detailed descriptions of one or more embodiments of the invention have been given above, various alternatives, modifications, and equivalents will be apparent to those skilled in the art without varying from the spirit of the invention. Therefore, the above description should not be taken as limiting the scope of the invention, which is defined by the appended claims.
Claims
What is claimed is:
1. A method comprising:
extracting behavior data of at least one subscriber account from outbound messages originated by said at least one subscriber account using a Sender Reputation Gateway (SRG) running on a computer system, said behavior data of said at least one subscriber account being attributes of said at least one subscriber account that are indicative of spam, virus, or worm related activity of said at least one subscriber account;
building a profile for said at least one subscriber account based on said behavior data extracted from said outbound messages originated by said at least one subscriber on said SRG running on said computer system;
tracking said behavior data extracted from said outbound messages originated by said at least one subscriber account using said SRG running on said computer system;
detecting behavior-based anomalies for said outbound messages originated by said at least one subscriber account using said SRG running on said computer system by comparing recent outbound messages originated by said at least one subscriber account with said profile of said at least one subscriber account to detect changes in said recent outbound messages originated by said at least one subscriber account in comparison to said profile of said at least one subscriber account;
determining reputation data for said at least one subscriber account based on said detected behavior-based anomalies using said SRG computer system, wherein the reputation data is added to the profile to determine a reputation score, and wherein if the reputation score falls below a threshold, then any subsequent outbound messages from the subscriber account are redirected to a server and prohibited from reaching their intended destination, and wherein the redirection to the server activity is designated for a specific time interval.
2. The method of claim 1 wherein said behavior data comprises at least one of a group consisting of: metrics relating to a size of said messages originated by said at least one subscriber account, metrics relating to a number of recipients specified by said messages originated by said at least one subscriber account, metrics relating to presence of attachments to said messages originated by said at least one subscriber account, metrics relating to timing of said messages originated by said at least one subscriber account, a total number of said messages originated by said at least one subscriber account, a total number of said messages originated by said at least one subscriber account suspected of being spam, a total number of said messages originated by said at least one subscriber account suspected of containing a virus, an average number of said messages originated by said at least one subscriber account, an average size of said messages originated by said at least one subscriber account, a largest size of said messages originated by said at least one subscriber account, a maximum size permitted for said messages originated by said at least one subscriber account, an average number of recipients for said messages originated by said at least one subscriber account, a largest number of recipients for said messages originated by said at least one subscriber account, a maximum number of recipients permitted for said messages originated by said at least one subscriber account, a frequency of repetition of recipients for said messages originated by said at least one subscriber account, an address format employed for said messages originated by said at least one subscriber account, an average number of message header lines for said messages originated by said at least one subscriber account, an average Bayesian spam filter score for said messages originated by said at least one subscriber account, a number of messages originated with attachments for said messages originated by said at least one subscriber account, a number of messages originated with particular attachment types for said messages originated by said at least one subscriber account, a number of messages originated by a particular mailer for said messages originated by said at least one subscriber account, a number of messages containing a particular character set for said messages originated by said at least one subscriber account, and standard deviations of various measurements of said messages originated by said at least one subscriber account behavior.
3. The method of claim 1 further comprising alerting a network operations analyst of said service provider of potential subscriber account misuse based on said detected behavior-based anomalies from said SRG running on said computer system.
4. The method of claim 1 comprising applying a predetermined set of message disposition policies to said messages originated by said at least one subscriber account based upon said determined reputation data for said at least one subscriber account using said SRG running on said computer system.
5. The method of claim 1 further comprising:
combining said reputation data determined based on said detected behavior-based anomalies for said at least one subscriber account with traditional content-based spam filtering reputation data for said at least one subscriber account to construct combined reputation data for said at least one subscriber account using said SRG running on said computer system;
taking an immediate action with regard to a particular message originated by said at least one subscriber account using said SRG running on said computer system in response to said combined reputation data; and
taking a long term action with regard to said at least one subscriber account using said SRG running on said computer system in response to said combined reputation data.
6. The method of claim 1 wherein said outbound communication medium is the Internet.
7. The method of claim 1 wherein said building of said profile for said at least one subscriber account is performed until there is sufficient behavior data to identify anomalies prior to said detecting of said behavior-based anomalies.
8. A sender reputation gateway system, comprising:
a service and response system that services and responds to requests from at least one subscriber account;
a behavior data extraction system that extracts behavior data of said at least one subscriber account from outbound messages originated by said at least one subscriber account, said behavior data of said at least one subscriber account being attributes of said at least one subscriber account that are indicative of spam, virus, or worm related activity;
a profile builder system that builds a profile for said at least one subscriber account based on said behavior data extracted from said outbound messages originated by said at least one subscriber;
a tracking system that tracks said behavior data extracted from said outbound messages originated by said at least one subscriber account;
an anomaly detection system that detects behavior-based anomalies for said outbound messages originated by said at least one subscriber account by comparing recent outbound messages originated by said at least one subscriber account with said profile of said at least one subscriber account to detect changes in said recent outbound messages originated by said at least one subscriber account in comparison to said profile of said at least one subscriber account; and
a reputation data determination system that determines reputation data for said at least one subscriber account based on said detected behavior-based anomalies, wherein the reputation data is added to the profile to determine a reputation score, and wherein if the reputation score falls below a threshold, then any subsequent outbound messages from the subscriber account are redirected to a server and prohibited from reaching their intended destination, and wherein the redirection to the server activity is designated for a specific time interval.
9. The sender reputation gateway system of claim 8 wherein said behavior data comprises at least one of a group consisting of: metrics relating to a size of said messages originated by said at least one subscriber account, metrics relating to a number of recipients specified by said messages originated by said at least one subscriber account, metrics relating to presence of attachments to said messages originated by said at least one subscriber account, metrics relating to timing of said messages originated by said at least one subscriber account, a total number of said messages originated by said at least one subscriber account, a total number of said messages originated by said at least one subscriber account suspected of being spam, a total number of said messages originated by said at least one subscriber account suspected of containing a virus, an average number of said messages originated by said at least one subscriber account, an average size of said messages originated by said at least one subscriber account, a largest size of said messages originated by said at least one subscriber account, a maximum size permitted for said messages originated by said at least one subscriber account, an average number of recipients for said messages originated by said at least one subscriber account, a largest number of recipients for said messages originated by said at least one subscriber account, a maximum number of recipients permitted for said messages originated by said at least one subscriber account, a frequency of repetition of recipients for said messages originated by said at least one subscriber account, an address format employed for said messages originated by said at least one subscriber account, an average number of message header lines for said messages originated by said at least one subscriber account, an average Bayesian spam filter score for said messages originated by said at least one subscriber account, a number of messages originated with attachments for said messages originated by said at least one subscriber account, a number of messages originated with particular attachment types for said messages originated by said at least one subscriber account, a number of messages originated by a particular mailer for said messages originated by said at least one subscriber account, a number of messages containing a particular character set for said messages originated by said at least one subscriber account, and standard deviations of various measurements of said messages originated by said at least one subscriber account behavior.
10. The sender reputation gateway system of claim 8 further comprising an alert system that alerts a network operations analyst of said service provider of potential subscriber account misuse based on said detected behavior-based anomalies.
11. The sender reputation gateway system of claim 8 further comprising a disposition policy system that applies a predetermined set of message disposition policies to said messages originated by said at least one subscriber account based upon said determined reputation data for said at least one subscriber account.
12. The sender reputation gateway system of claim 8 wherein said reputation data determination system further combines said reputation data determined based on said detected behavior-based anomalies for said at least one subscriber account with traditional content-based spam filtering reputation data for said at least one subscriber account to construct combined reputation data for said at least one subscriber account; takes an immediate action with regard to a particular message originated by said at least one subscriber account in response to said combined reputation data; and takes a long term action with regard to said at least one subscriber account in response to said combined reputation data.
13. The sender reputation gateway system of claim 8 wherein said outbound communication medium is the Internet.
14. The sender reputation gateway system of claim 8 wherein said profile builder system operates until there is sufficient behavior data to identify anomalies prior to operating said anomaly detection system.
15. A machine-readable medium that stores instructions for a computer system to perform sender reputation gateway processes, comprising:
extracting behavior data of at least one subscriber account from outbound messages originated by said at least one subscriber account, said behavior data of said at least one subscriber account being attributes of said at least one subscriber account that are indicative of spam, virus, or worm related activity of said at least one subscriber account that results in outbound message abuse of the service provider;
building a profile for said at least one subscriber account based on said behavior data extracted from said outbound messages originated by said at least one subscriber;
tracking said behavior data extracted from said outbound messages originated by said at least one subscriber account;
detecting behavior-based anomalies for said outbound messages originated by said at least one subscriber account by comparing recent outbound messages originated by said at least one subscriber account with said profile of said at least one subscriber account to detect changes in said recent outbound messages originated by said at least one subscriber account in comparison to said profile of said at least one subscriber account;
determining reputation data for said at least one subscriber account based on said detected behavior-based anomalies, wherein the reputation data is added to the profile to determine a reputation score, and wherein if the reputation score falls below a threshold, then any subsequent outbound messages from the subscriber account are redirected to a server and prohibited from reaching their intended destination, and wherein the redirection to the server activity is designated for a specific time interval.
16. The machine-readable medium of claim 15 wherein said behavior data comprises at least one of a group consisting of: metrics relating to a size of said messages originated by said at least one subscriber account, metrics relating to a number of recipients specified by said messages originated by said at least one subscriber account, metrics relating to presence of attachments to said messages originated by said at least one subscriber account, metrics relating to timing of said messages originated by said at least one subscriber account, a total number of said messages originated by said at least one subscriber account, a total number of said messages originated by said at least one subscriber account suspected of being spam, a total number of said messages originated by said at least one subscriber account suspected of containing a virus, an average number of said messages originated by said at least one subscriber account, an average size of said messages originated by said at least one subscriber account, a largest size of said messages originated by said at least one subscriber account, a maximum size permitted for said messages originated by said at least one subscriber account, an average number of recipients for said messages originated by said at least one subscriber account, a largest number of recipients for said messages originated by said at least one subscriber account, a maximum number of recipients permitted for said messages originated by said at least one subscriber account, a frequency of repetition of recipients for said messages originated by said at least one subscriber account, an address format employed for said messages originated by said at least one subscriber account, an average number of message header lines for said messages originated by said at least one subscriber account, an average Bayesian spam filter score for said messages originated by said at least one subscriber account, a number of messages originated with attachments for said messages originated by said at least one subscriber account, a number of messages originated with particular attachment types for said messages originated by said at least one subscriber account, a number of messages originated by a particular mailer for said messages originated by said at least one subscriber account, a number of messages containing a particular character set for said messages originated by said at least one subscriber account, and standard deviations of various measurements of said messages originated by said at least one subscriber account behavior.
17. The machine-readable medium of claim 15 further comprising alerting a network operations analyst of said service provider of potential subscriber account misuse based on said detected behavior-based anomalies.
18. The machine-readable medium of claim 15 further comprising applying a predetermined set of message disposition policies to said messages originated by said at least one subscriber account based upon said determined reputation data for said at least one subscriber account.
19. The machine-readable medium of claim 15 further comprising:
combining said reputation data determined based on said detected behavior-based anomalies for said at least one subscriber account with traditional content-based spam filtering reputation data for said at least one subscriber account to construct combined reputation data for said at least one subscriber account;
taking an immediate action with regard to a particular message originated by said at least one subscriber account in response to said combined reputation data; and taking a long term action with regard to said at least one subscriber account in response to said combined reputation data.
Patent Citations (143)
| Patent | Date | Inventor | Cited By |
|---|---|---|---|
| US5627764(A) | 1997-05-01 | Schutzman et al. | Applicant |
| US5790790(A) | 1998-08-01 | Smith et al. | Applicant |
| US5884033(A) | 1999-03-01 | Duvall et al. | Applicant |
| US5937161(A) | 1999-08-01 | Mulligan et al. | Applicant |
| US5937162(A) | 1999-08-01 | Funk et al. | Applicant |
| US6003027(A) | 1999-12-01 | Prager | Applicant |
| US6052709(A) | 2000-04-01 | Paul | Applicant |
| US6061448(A) | 2000-05-01 | Smith et al. | Applicant |
| US6119137(A) | 2000-09-01 | Smith et al. | Applicant |
| US6141686(A) | 2000-10-01 | Jackowski et al. | Applicant |
| US6151675(A) | 2000-11-01 | Smith | Applicant |
| US6161130(A) | 2000-12-01 | Horvitz et al. | Applicant |
| US6192360(B1) | 2001-02-01 | Dumais et al. | Applicant |
| US6192407(B1) | 2001-02-01 | Smith et al. | Applicant |
| US6249805(B1) | 2001-06-01 | Fleming, III | Applicant |
| US6266692(B1) | 2001-07-01 | Greenstein | Applicant |
| US6321267(B1) | 2001-11-01 | Donaldson | Applicant |
| US6381634(B1) | 2002-04-01 | Tello et al. | Applicant |
| US6385655(B1) | 2002-05-01 | Smith et al. | Applicant |
| US6389455(B1) | 2002-05-01 | Fuisz | Applicant |
| US6393465(B2) | 2002-05-01 | Leeds | Applicant |
| US6400810(B1) | 2002-06-01 | Skladman et al. | Applicant |
| US6421709(B1) | 2002-07-01 | McCormick et al. | Applicant |
| US6438583(B1) | 2002-08-01 | McDowell et al. | Applicant |
| US6460050(B1) | 2002-10-01 | Pace et al. | Applicant |
| US6470086(B1) | 2002-10-01 | Smith | Applicant |
| US6487599(B1) | 2002-11-01 | Smith et al. | Applicant |
| US6493007(B1) | 2002-12-01 | Pang | Applicant |
| US6507866(B1) | 2003-01-01 | Barchi | Applicant |
| US6529956(B1) | 2003-03-01 | Smith et al. | Applicant |
| US6546416(B1) | 2003-04-01 | Kirsch | Applicant |
| US6587549(B1) | 2003-07-01 | Weik | Applicant |
| US6609196(B1) | 2003-08-01 | Dickinson, III et al. | Applicant |
| US6615241(B1) | 2003-09-01 | Miller et al. | Applicant |
| US6615242(B1) | 2003-09-01 | Riemers | Applicant |
| US6618747(B1) | 2003-09-01 | Flynn et al. | Applicant |
| US6643686(B1) | 2003-11-01 | Hall | Applicant |
| US6643687(B1) | 2003-11-01 | Dickie et al. | Applicant |
| US6643688(B1) | 2003-11-01 | Fuisz | Applicant |
| US6650890(B1) | 2003-11-01 | Irlam et al. | Applicant |
| US6651166(B1) | 2003-11-01 | Smith et al. | Applicant |
| US6654787(B1) | 2003-11-01 | Aronson et al. | Applicant |
| US6711615(B2) | 2004-03-01 | Porras et al. | Applicant |
| US6725381(B1) | 2004-04-01 | Smith et al. | Applicant |
| US6732101(B1) | 2004-05-01 | Cook | Applicant |
| US6732157(B1) | 2004-05-01 | Gordon et al. | Applicant |
| US6748529(B2) | 2004-06-01 | Smith | Applicant |
| US6757830(B1) | 2004-06-01 | Tarbotton et al. | Applicant |
| US6769016(B2) | 2004-07-01 | Rothwell et al. | Applicant |
| US6772196(B1) | 2004-08-01 | Kirsch et al. | Applicant |
| US6802012(B1) | 2004-10-01 | Smithson et al. | Applicant |
| US6826609(B1) | 2004-11-01 | Smith et al. | Applicant |
| US6829635(B1) | 2004-12-01 | Townshend | Applicant |
| US6842773(B1) | 2005-01-01 | Ralston et al. | Applicant |
| US6850602(B1) | 2005-02-01 | Chou | Applicant |
| US6868498(B1) | 2005-03-01 | Katsikas | Applicant |
| US6901509(B1) | 2005-05-01 | Kocher | Applicant |
| US6907571(B2) | 2005-06-01 | Slotznick | Applicant |
| US6912285(B2) | 2005-06-01 | Jevans | Applicant |
| US6941348(B2) | 2005-09-01 | Petry et al. | Applicant |
| US6944616(B2) | 2005-09-01 | Ferguson et al. | Applicant |
| US6963929(B1) | 2005-11-01 | Lee | Applicant |
| US7016939(B1) | 2006-03-01 | Rothwell et al. | Applicant |
| US7020642(B2) | 2006-03-01 | Ferguson et al. | Applicant |
| US7051077(B2) | 2006-05-01 | Lin | Applicant |
| US7062498(B2) | 2006-06-01 | Al-Kofahi et al. | Applicant |
| US7072942(B1) | 2006-07-01 | Maller | Applicant |
| US7089241(B1) | 2006-08-01 | Alspector et al. | Applicant |
| US7107254(B1) | 2006-09-01 | Dumais et al. | Applicant |
| US7145875(B2) | 2006-12-01 | Allison et al. | Applicant |
| US7178030(B2) | 2007-02-01 | Scheidt et al. | Applicant |
| US7181764(B2) | 2007-02-01 | Zhu et al. | Applicant |
| US7219148(B2) | 2007-05-01 | Rounthwaite et al. | Applicant |
| US7266508(B1) | 2007-09-01 | Owen et al. | Applicant |
| US7320020(B2) | 2008-01-01 | Chadwick et al. | Applicant |
| US7360165(B2) | 2008-04-01 | Cortright et al. | Applicant |
| US7401148(B2) | 2008-07-01 | Lewis | Applicant |
| US7472422(B1) | 2008-12-01 | Agbabian | Examiner |
| US7596600(B2) | 2009-09-01 | Quine et al. | Applicant |
| US7657935(B2) | 2010-02-01 | Stolfo et al. | Applicant |
| US7680890(B1) | 2010-03-01 | Lin | Applicant |
| US2002/0007453(A1) | 2002-01-01 | Nemovicher | Applicant |
| US2002/0120697(A1) | 2002-08-01 | Generous et al. | Applicant |
| US2002/0188863(A1) | 2002-12-01 | Friedman | Applicant |
| US2002/0199095(A1) | 2002-12-01 | Bandini et al. | Applicant |
| US2003/0009698(A1) | 2003-01-01 | Lindeman et al. | Applicant |
| US2003/0023736(A1) | 2003-01-01 | Abkemeier | Applicant |
| US2003/0061506(A1) | 2003-03-01 | Cooper et al. | Applicant |
| US2003/0074413(A1) | 2003-04-01 | Nielsen et al. | Applicant |
| US2003/0158905(A1) | 2003-08-01 | Petry et al. | Applicant |
| US2003/0172294(A1) | 2003-09-01 | Judge | Examiner |
| US2003/0177387(A1) | 2003-09-01 | Osterwalder et al. | Applicant |
| US2003/0187937(A1) | 2003-10-01 | Yao et al. | Applicant |
| US2003/0212546(A1) | 2003-11-01 | Shaw | Examiner |
| US2004/0058673(A1) | 2004-03-01 | Irlam et al. | Applicant |
| US2004/0088369(A1) | 2004-05-01 | Yeager et al. | Applicant |
| US2004/0088551(A1) | 2004-05-01 | Dor et al. | Applicant |
| US2004/0177120(A1) | 2004-09-01 | Kirsch | Applicant |
| US2004/0177271(A1) | 2004-09-01 | Arnold et al. | Applicant |
| US2004/0199597(A1) | 2004-10-01 | Libbey et al. | Applicant |
| US2005/0010644(A1) | 2005-01-01 | Brown et al. | Examiner |
| US2005/0015626(A1) | 2005-01-01 | Chasin | Applicant |
| US2005/0021649(A1) | 2005-01-01 | Goodman et al. | Examiner |
| US2005/0044153(A1) | 2005-02-01 | Gross | Applicant |
| US2005/0044170(A1) | 2005-02-01 | Cox et al. | Applicant |
| US2005/0063365(A1) | 2005-03-01 | Mathew et al. | Examiner |
| US2005/0064850(A1) | 2005-03-01 | Irlam et al. | Applicant |
| US2005/0076084(A1) | 2005-04-01 | Loughmiller et al. | Applicant |
| US2005/0080816(A1) | 2005-04-01 | Shipp | Applicant |
| US2005/0081059(A1) | 2005-04-01 | Bandini et al. | Applicant |
| US2005/0091272(A1) | 2005-04-01 | Smith et al. | Applicant |
| US2005/0125667(A1) | 2005-06-01 | Sullivan et al. | Applicant |
| US2005/0149747(A1) | 2005-07-01 | Wesinger et al. | Applicant |
| US2005/0182959(A1) | 2005-08-01 | Petry et al. | Applicant |
| US2005/0182960(A1) | 2005-08-01 | Petry et al. | Applicant |
| US2005/0198182(A1) | 2005-09-01 | Prakash et al. | Applicant |
| US2005/0240617(A1) | 2005-10-01 | Lund et al. | Applicant |
| US2005/0259667(A1) | 2005-11-01 | Vonokurov et al. | Applicant |
| US2005/0266832(A1) | 2005-12-01 | Irlam et al. | Applicant |
| US2006/0031483(A1) | 2006-02-01 | Lund et al. | Applicant |
| US2006/0039540(A1) | 2006-02-01 | Issinski | Applicant |
| US2006/0047766(A1) | 2006-03-01 | Spadea | Applicant |
| US2006/0075497(A1) | 2006-04-01 | Garg | Applicant |
| US2006/0080432(A1) | 2006-04-01 | Spataro et al. | Applicant |
| US2006/0080613(A1) | 2006-04-01 | Savant | Applicant |
| US2006/0168006(A1) | 2006-07-01 | Shannon et al. | Applicant |
| US2006/0168024(A1) | 2006-07-01 | Mehr et al. | Examiner |
| US2006/0168057(A1) | 2006-07-01 | Warren et al. | Applicant |
| US2006/0277220(A1) | 2006-12-01 | Patrick et al. | Applicant |
| US2006/0277597(A1) | 2006-12-01 | Dreymann | Applicant |
| US2007/0008987(A1) | 2007-01-01 | Manion et al. | Applicant |
| US2007/0044152(A1) | 2007-02-01 | Newman et al. | Applicant |
| US2007/0067392(A1) | 2007-03-01 | Torres et al. | Applicant |
| US2007/0106698(A1) | 2007-05-01 | Elliott et al. | Applicant |
| US2007/0107059(A1) | 2007-05-01 | Chasin et al. | Applicant |
| US2007/0214227(A1) | 2007-09-01 | Quinn | Applicant |
| US2007/0244974(A1) | 2007-10-01 | Chasin | Applicant |
| US2010/0030858(A1) | 2010-02-01 | Chasin | Applicant |
| EP1949240 | 2008-07-01 | Applicant | |
| JP2009515426 | 2009-04-01 | Applicant | |
| WO2005/006139 | 2005-01-01 | Applicant | |
| WO2005/010692 | 2005-02-01 | Applicant | |
| WO2007/055770 | 2007-05-01 | Applicant |
Non-Patent Literature (49)
- Final Office Action mailed May 27, 2009 in U.S. Appl. No. 10/888,370, filed Jul. 9, 2004, by C. Scott Chasin.Applicant
- Non-Final Office Action mailed Sep. 22, 2008 in U.S. Appl. No. 10/888,370, filed Jul. 9, 2004, by C. Scott Chasin.Applicant
- Final Office Action mailed Jan. 16, 2008 in U.S. Appl. No. 10/888,370, filed Jul. 9, 2004, by C. Scott Chasin.Applicant
- Non-Final Office Action mailed Jul. 31, 2007 in U.S. Appl. No. 10/888,370, filed Jul. 9, 2004, by C. Scott Chasin.Applicant
- Non-Final Office Action mailed Apr. 28, 2009 in U.S. Appl. No. 11/372,970, filed Mar. 10, 2006, by C. Scott Chasin.Applicant
- Final Office Action mailed Apr. 27, 2009 in U.S. Appl. No. 11/315,480, filed Dec. 21, 2005, by C. Scott Chasin.Applicant
- Non-Final Office Action mailed Sep. 17, 2008 in U.S. Appl. No. 11/315,480, filed Dec. 21, 2005, by C. Scott Chasin.Applicant
- Non-Final Office Action mailed May 11, 2009 in U.S. Appl. No. 11/537,432, filed Sep. 29, 2006, by C. Scott Chasin.Applicant
- Non-Final Office Action mailed Oct. 6, 2008 in U.S. Appl. No. 11/394,890, filed Mar. 31, 2006, by Wei Lin.Applicant
- Woitaszek, M.; Shaaban, M.; Czernikowski, R., “Identifying junk electronic mail in Microsoft outlook with a support vector machine,” Proceedings of the 2003 Symposium on Application and the Internet, Jan. 2003.Applicant
- International Preliminary Report on Patentability and Written Opinion of the International Search Authority for PCT/US2006/32402, International Searching Authority, Mar. 24, 2009.Applicant
- Corporate Factsheet 2005, Clearswift Ltd., downloaded Nov. 6, 2005 (12 pages).Applicant
- Zachariassen, Rayan, ZMailer The Manual, v.1.99.26.200602020935, available http://www.zmailer.org/zman/zmanual.shtml, downloaded Apr. 26, 2006 (312 pages).Applicant
- Sendmail. Inc., Sendmail.org home page, available at http://www.sendmail.org/, downloaded Nov. 6, 2005.Applicant
- Lindberg, G., RFC 2505—Anti-Spam Recommendations for SMTP MTAs, The Internet Society, Feb. 1999, available at http://www.faqs.org/rfcs/rfc2505.html, downloaded Nov. 6, 2005.Applicant
- Postfix.org web site, available at http://www.postfix.org, downloaded Nov. 6, 2005.Applicant
- Mail Abuse Prevention System, LLC, Basic Mailing List Management Guidelines for Preventing Abuse, available at http://web.archive.org/web/20010309004654/maps.vix.com/manage.html, downloaded Nov. 6, 2005.Applicant
- Stolfo, Salvatore J., et al., research paper, “Combining Behavior Models to Secure E-Mail Systems,” Columbia University, May 16, 2003.Applicant
- Bhattacharyya, Manasi, et al., research paper, “MET: An Experimental System for Malicious Email Tracking,” Columbia University and Cornell University.Applicant
- Gupta, A., et al., research paper, “An Approach for Detecting Self-Propogating Email Using Anamoly Detection,” Department of Computer Science, Stony Brook University.Applicant
- Stolfo, Salvatore J., et al., research paper, “Detecting Viral Propagations Using Email Behavior Profiles,” Columbia University.Applicant
- “Allegro's Mailzone Stops Back Orifice 2000,” Allegro.net press release, Jul. 15, 1999, available at www.webarchive.org, downloaded Apr. 29, 2006.Applicant
- “Allegro's Mailzone Stops Back Orifice 2000,” Allegro.net press release, Jul. 14, 1999, available at www.webarchive.org, downloaded Apr. 29, 2006, available at www.webarchive.org, downloaded Apr. 29, 2006.Applicant
- “Allegro's Mailzone Blocks Illegal MP3 Files,” Allegro.net press release, Jul. 14, 1999, www.webarchive.org, downloaded Apr. 29, 2006.Applicant
- “Allegro's Mailzone Stops ‘Worn’ While on the 'Net,” Allegro.net press release, Jun. 10, 1999, available at www.webarchive.org, downloaded Apr. 29, 2006.Applicant
- “Allegro's Richard Bliss to speak at upcoming ‘E-mail Outsourcing’ conference,” Allegro.net press release Jun. 2, 1999, available at www.webarchive.org, downloaded Apr. 29, 2006.Applicant
- “‘Phantom Menace’ a real menace to network administration,” Allegro.net press release, Apr. 28, 1999, available at www.webarchive.org, downloaded Apr. 29, 2006.Applicant
- “Allegro Mailzone Filters Junk E-Mail,” Law Technology Product News, vol. 6, Issue 3, Mar. 1999, available at www.webarchive.org, downloaded Apr. 29, 2006.Applicant
- Thyfault, Mary E., “Companies choose outside e-mail services for cost, functionality, and easy administration,” Information Week, Aug. 2, 1999, available at www.informationweek.com, downloaded Apr. 29, 2006.Applicant
- “Allegro messaging company has protected 1,000 businesses from viruses,” Dayton Business Journal, Jun. 11, 1999, available at www.dayton.bizjornals.com, downloaded Apr. 29, 2006.Applicant
- McNamara, Paul, “Take my apps—please,” NetworkWorld, May 31, 1999, available at www.networkworld.com, downloaded Apr. 29, 2006.Applicant
- Mailzone Web Site, available at www.webarchive.org, downloaded Apr. 29, 2006.Applicant
- Listserv 14.5 @ Miami University, “Allegro Mailzone Filters Unwanted E-Mail,” Jan. 25, 1999, available at www.listserv.muohio.edu, downloaded Apr. 29, 2006.Applicant
- “Allegro's Mailzone Stops Back Orifice 2000,” Allegro.net press release Jul. 14, 1999, available at www.webarchive.org, downloaded Apr. 29, 2006 (2 pages).Applicant
- Graham, Better Bayesian Filtering, Jan. 2003 (12 pages).Applicant
- International Search Report for PCT/US2006/32402, International Searching Authority, Mar. 25, 2008 (2 pages).Applicant
- International Search Report mailed Aug. 4, 2006 (2 pages), International Preliminary Report on Patentability issued Oct. 3, 2006 (1 page), and Written Opinion of the International Searching Authority mailed Aug. 4, 2006 (3 pages) for International Application No. PCT/US04/20899 (6 pages).Applicant
- International Search Report mailed Dec. 2, 2009 (1 page), International Preliminary Report on Patentability issued Feb. 17, 2009 (1 page), and Written Opinion of the International Searching Authority mailed Dec. 2, 2009 (5 pages), for International Application No. PCT/US04/22846 (7 pages).Applicant
- M. Sahami, S. Dumais, D. Heckerman, and E. Horvitz, “A Bayesian approach to filtering junk e-mail”, In Learning for Text Categorization—Papers from the AAAI Workshop, pp. 55-62, Madison, Wisconsin, 1998 (8 pages).Applicant
- Nonfinal Office Action mailed Aug. 4, 2009 in U.S. Appl. No. 11/365,130, filed Feb. 28, 2006 (10 pages).Applicant
- Sergeant, Internet Level Spam Detection and SpamAssassin 2.50, MessageLabs, http://spamassassin.apache.org/presentations/SpamConf2003.pdf, 2003 (21 pages).Applicant
- U.S. Appl. No. 11/372,970, filed Mar. 10, 2006.Applicant
- U.S. Appl. No. 11/315,480, filed Dec. 21, 2005.Applicant
- U.S. Appl. No. 11/394,890, filed Mar. 31, 2006.Applicant
- U.S. Appl. No. 11/465,433, filed Aug. 17, 2006.Applicant
- U.S. Appl. No. 11/537,432, filed Sep. 29, 2006.Applicant
- U.S. Appl. No. 60/886,898, filed Jan. 26, 2007.Applicant
- Peer-to-Peer (P2P) Roadmap; Website: http://msdn2.microsoft.com/en-us/library/bb756997(printer).aspx, date retrieved Feb. 1, 2008, 4 pages.Applicant
- People Near Me; Microsoft TechNet, Website: http://technet.microsoft.com/en-us/library/bb726969(printer).aspx, published Sep. 27, 2006, date retrieved Feb. 1, 2008, 6 pages.Applicant