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The invention relates to dynamic message filtering, such as for example filtering incoming messages in response to their content; in one embodiment, mes- sages can be delivered, or other action taken, in response to a result of dynamic fil- tering. In computer communication networks, it is common to send and re- ceive messages among users, such as for the purpose of correspondence, distributing information, and responding to requests.
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One method for doing so is electronic mail, also known as email. One problem that has arisen in the art is that some messages are unwanted. Moreover, it has become common for advertisers and other message senders to collect relatively large numbers of email addresses, and to send unsolicited advertising in bulk to recipients at those email addresses.
When the number of such unsolicited bulk email messages is relatively large, it can take substantial time and effort for recipients to delete them.
There is also the possibility that the recipient will miss a relatively important message due to the relatively large number of unimpor- tant messages accumulated in their email inbox.
Such unsolicited bulk email mes- sages are often known by the colloquial term "spam," and senders of such messages are often known as "spammers. While these methods generally achieve the goal of filtering messages, they are subject to the drawback that the user is involved in managing the whitelist or blacklist, and the further drawback that spammers often choose new, unique, sending addresses from which to send new spam.
A second known method for detecting spam includes attempting to evaluate from the content of the message whether it is spam or not.
Known evalua- tion techniques include a searching the message for known keywords that are typi- cally indicative of spam, such as words identifying known products popularly pro- moted by spammers, and b evaluating the message by comparing the number of such "bad" keywords with probable "good" keywords, such as words relatively unlikely to be used in a spam message.
One example of the latter method is the Bayesian filter proposed by Paul Graham, "A Plan for Spam," and performed by some implementations of the "Mozilla" email client. While these methods generally achieve the goal of filtering messages, they are subject to the drawback that the user must train the implementation to recognize the "bad" keywords and "good" keywords par- ticular to the type of message that user typically receives, and the further drawback that spammers often choose, new, unique, products to promote or words often mis- spellings with which to identify them.
Accordingly, it would be advantageous to provide an improved tech- nique for dynamic message filtering. The invention provides a method and system capable of dynamically filtering incoming messages, with the effect of classifying those messages into one of at least three categories: good messages, bulk periodicals, and spam.
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The intermedi- ate category of "bulk periodicals" is reserved for messages that are clearly not directed to the individual recipient, but which the recipient might wish to review anyway, such as for example information relating to updates of products the user is already using, or information relating to products or services the user is explicitly interested in.
In a first aspect, the system includes an identification engine that clas- sifies messages based on a measured intent of each message. In one embodiment, the engine includes a regular expression recognizer and a set of artificial neural networks pre-trained to classify messages. The regular expression recognizer is suitable for detecting misspelled words, likely spam phrases composed of otherwise innocent words such as for example "MAKE MONEY FAST" , and other common attempts by spammers to evade detection by known keywords that are typically indicative of spam.
The artificial neural networks divide messages into "likely good" and "likely spam," and with that information, operate at a more detailed and discriminating level to distinguish among good messages, bulk periodicals, and spam.
Messages initially considered "likely good" might be ultimately identified as good messages or as bulk periodicals. Similarly, messages initially considered "likely spam" might be ulti- mately identified as bulk periodicals or as spam. This aspect accounts for the fuzzi- ness in determination, and reduces the number of messages erroneously identified as spam by identifying a significant number of them as bulk periodicals, which are con- sidered relatively less pernicious by the user.
In a second aspect, the system includes a dynamic whitelist and black- list, into which sending addresses are collected when the number of messages from those sending addresses indicates that the sender is likely good or likely a spammer. In one embodiment, any sender for whom at least a threshold number preferably four of messages pass as good messages is automatically added to the whitelist of known good senders, so that messages from those senders need not be checked as thoroughly as from other senders.
EP1714201A4 - Dynamic message filtering - Google Patents
In a third aspect, the system includes a set of regular expressions whose detection is input to the artificial neural networks, in one embodiment selected before installation, with the effects that the artificial neural networks can be trained more rapidly, and respond more rapidly and accurately to changes in the typical email re- ceived by the user. In one embodiment, a subset of the 2, most useful regular expressions identifying words or phrases is selected using a genetic algorithm, out of the possibly 70, most common English words and phrases that might be used.
This also has the effect that the artificial neural networks can be made smaller that is, with fewer input nodes and fewer hidden nodes , and are capable of being executed directly in relatively less main memory, with the effect that such execution is rela- tively faster.
Figure l shows a block diagram of a generalized system for dynamic message filtering. Figure 2 shows a block diagram of a system for dynamic message fil- tering, in an embodiment disposed behind a firewall. Figure 3 shows a block diagram of a system for dynamic message fil- tering, in an embodiment disposed as a server.
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Figure 5 shows a flow diagram of a method for dynamic message filter- ing. In the description herein, a preferred embodiment of the invention is described, including preferred process steps and data structures. Those skilled in the art would realize, after perusal of this application, that embodiments of the invention might be implemented using a variety of other techniques not specifically described, without undue experimentation or further invention, and that such other techniques would be within the scope and spirit of the invention.
The general meaning of each of these following terms is intended to be illustrative and in no way limiting. As used herein, the term "message" is intentionally broad. As described herein, there is no particular requirement that messages must be pure or primarily text. As used herein, the term "spam" is intentionally broad, even though it might be typically applied to messages that are unsolicited, sent in bulk, and often involve advertising.
This has the effect that the invention provides a method and system capable of dy- namically filtering incoming messages, with the effect of classifying those messages into one of at least three categories: good messages, bulk periodicals, and spam. The former are relatively important messages, the latter are relatively unwanted messages, and the middle bulk periodicals are messages that might or might not be desirable to the user.
For example, not intended to be limiting in any way, "taking action" in response to that evaluation might include forwarding part or all of a message to a wireless recipient, copying the message to a more permanent log, redistributing the message to another user, or reporting the sender of the message to an anti-spam enforcer such as for example the spammer's ISP, a common blacklist of spammer sending addresses, or a government agency.
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Other and further applications of the invention, including extensions of these terms and concepts, would be clear to those of ordinary skill in the art after purchasing this application. These other and further applications are part of the scope and spirit of the invention, and would be clear to those of ordinary skill in the art without further invention or undue experimentation. The scope and spirit of the invention is not limited to any of these defi- nitions, or to specific examples mentioned therein, but is intended to include the most general concepts embodied by these and other terms.
In a generalized conception of an embodiment of the invention, a sys- tem loo is coupled to an outside network no, and includes an appliance level , a server level , and a client level The outside network might include any technique for sending or receiving messages, including incoming mail traffic such as email and other mes- sages.
In one embodiment, the outside network no includes an Internet, such as for example an ISP coupled to an Internet backbone network. However, in the context of the invention, there is no particular requirement that the outside network no in- volves any particular type of communication system.
In alternative embodiments, the outside network may include an intranet, extranet, VPN, an ATM network, a pri- vate or public switched network such as for example a PSTN, or some combination or conjunction thereof. In one embodiment, the appliance level includes an entry point to an enterprise network, possibly involving a firewall, a router or gateway router, or a software construct such as a VPN virtual private network disposed within a more inclusive communication network.
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The appliance level includes a spam filter coupled to the entry point to the enterprise network, and also coupled to the rest of the enterprise network. For one example, not intended to be limiting in any way, the spam filter might be coupled to the firewall at a first port , and coupled to the enterprise network such as a network including a LAN, WAN, VLAN, VPN, or the like at a second port In one embodiment, the spam filter includes at least some storage , such as for example a database or other storage, at which the spam filter might maintain any junk mail spam blocked, retained, or withheld by the spam filter In one embodiment, the server level includes a set of server ele- ments.
For example, not intended to be limiting in any way, the server level might include at least one of: a mail server, a web server, a database server, a server for network-attached storage, or a print server. In one embodiment, the server level includes at least one mail server , which is coupled to the spam filter at a first port , and coupled to the client level at a second port For example, not intended to be limiting in any way, the mail server might be coupled to a set of workstations at which users receive and manipulate email messages.
In one embodiment, the client level includes a set of client devices. For example, not intended to be limiting in any way, the client level might include a set of workstations, printers, wireless communication devices, or handheld devices such as for example "Blackberry" or "Palm Pilot" devices or PDA's personal digital assistants or personal organizers. In one embodiment, the client level includes at least one recipient mailbox The recipient mailbox includes at least two re- gions, a "good messages" mailbox section and a "bulk periodicals" mailbox sec- tion As described below, the spam filter receives at least some of the in- coming mail traffic ill from the outside network , and classifies messages from that incoming mail traffic into a set of classes.
In one embodiment, this set of classes includes "good messages," "bulk periodicals," and "junk email.
At the server level , the mail server receives the good messages or bulk periodicals, suitably marked, delivers the good messages to the "good messages" mailbox section , and delivers the bulk periodicals to the "bulk periodicals" mailbox section An embodiment of a system includes an outside network similar to the outside network of figure 1 , a firewall similar to the firewall, router or gateway router described with regard to the appliance level of figure 1 , a mail server similar to the mail server of figure 1 , an administrator web client , an end-user web client , and a spam filter similar to the spam fil- ter of figure 1.
Similar to the outside network of figure 1, the outside network might include any technique for sending or receiving messages.
In one embodiment, the outside network includes an Internet, such as for example an ISP coupled to an Internet backbone network. However, in the context of the invention, there is no particular requirement that the outside network involves any particular type of communication system.
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In alternative embodiments, the outside network may include an intranet, extranet, VPN, an ATM network, a private or public switched network such as for example a PSTN, or some combination or conjunction thereof. Similar to the firewall described with regard to the appliance level of figure 1, the firewall is capable of receiving mail traffic such as email and other messages from the outside network , examining those messages to de- termine if they should be blocked or not in response to a set of firewall rules main- tained by the firewall , and sending those messages if not blocked to the spam filter Similar to the mail server of figure 1, the mail server is capable of receiving messages from the spam filter and forwarding those messages to end-user recipients in response to their contents.
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The administrator web client includes a processor, program and data memory, and input and output devices, such as for example configured as a desktop workstation, a notebook computer, a "Blackberry" or "Palm Pilot" or other handheld computing device, or other device.
The administrator web client is ca- pable of communicating with the spam filter , with the effect than an adminis- trator is capable of reviewing, editing, or deleting configuration information main- tained by the spam filter for general use.
The end-user web client includes a processor, program and data memory, and input and output devices, such as for example configured as a desktop workstation, a notebook computer, a "Blackberry" or "Palm Pilot" or other handheld computing device, or other device. The end-user web client is capable of com- municating with the spam filter , with the effect than an end-user is capable of reviewing, editing, or deleting configuration information maintained by the spam fil- ter for use involving that end-user.
Similar to the spam filter of figure 1, the spam filter is capable of receiving the messages allowed through by the firewall , examining those messages to determine if they should be treated as good messages, bulk adver- tising, or spam, and taking one or more actions with regard to those messages in response to a result of that determination.
Those one or more actions might include a tagging the message appropriately before forwarding it to the mail server for delivery, b delaying, deleting, quarantining, or otherwise treating the message , c forwarding the message to users or other entities besides the end-user to whom the message was originally addressed, and d updating its own state with the effect that the spam filter is better able to discern which messages are good messages, bulk advertising, or spam.
In one embodiment, the spam filter includes a mail transfer agent , a database , an identification engine , an administration interface element , an end-user interface element , a web server , a web CGI layer , an operating system layer , and a hardware platform In one embodiment, the mail transfer agent includes a PostFix Mail Transfer Agent, such as for example a version 1.
The mail transfer agent could also use or instead include Sendmail.
The mail transfer agent is capable of transferring messages among or between devices, using the general schema that user senders using user agents send messages to the mail transfer agent , which sends the message to one or more other mail transfer agents, each of which delivers the message to one or more end-user recipients.
In one embodiment, the mail transfer agent is modified with the effect that it communicates with the database and the iden- tification engine to examine and classify messages In one embodiment, the database is used to store user and administra- tive settings, as well as statistics and email logging and reporting. Messages that are identified as spam can also be stored in a file system for later retrieval if a user de- termines that the messages are not actually spam that is, they were misidentified "false positives".
In alternative embodiments, messages that are identified as spam can also be stored in the database for later retrieval under similar conditions. In one embodiment, the identification engine includes a Corvigo proprietary filtering engine, such as for example version 2.
In this em- bodiment, the filtering engine uses a combination of artificial intelligence techniques, for example including natural language processing, to determine the intent of mes- sages. Filtering can then be performed based on determined intent.
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In one embodiment, the administration interface element includes an interface. The administrator interface element allows an administrator to config- ure, run and maintain the spam filter In one embodiment, the end-user interface element includes a user interface. The user interface element allows users to perform one or more of the fol- lowing operations: modifying their spam filtering preferences, viewing a report of mail messages and how that mail was categorized and handled, and allowing the us- ers to find and retrieve "false positives" that is, good messages mistakenly identified as bulk periodicals or spam.
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In this embodiment, the web server provides functions and interfaces used to generate a web CGI layer such as web CGI layer In a first preferred embodiment, the hardware platform and the operating system layer include an Intel-architecture processor or a functional equivalent thereof operating under control of a version of the Linux operating system or a similar operating system, such as a version of Unix or an operating system in- eluding the Mach microkernel.
In a second preferred embodiment, the hardware platform and the operating system layer include a Sun SPARC station proc- essor or a functional equivalent thereof operating under control of a version of the Solaris operating system or a similar operating system, such as a version of Unix. As described below, in one embodiment the mail transfer agent at the spam filter receives at least some of the messages from the outside net- work , such as for example possibly using the firewall The messages are routed to the identification engine for classification based on an intent of each message, as determined by that identification engine The artificial neural networks divide messages into "likely good" and "likely spam," and with that information, operate at a more detailed and discriminating level to distinguish among good messages, bulk periodi- cals, and spam.