Systems and methods for classification of messaging entities

Abstract

Methods and systems for operation upon one or more data processors for assigning a reputation to a messaging entity. A method can include receiving data that identifies one or more characteristics related to a messaging entity's communication. A reputation score is determined based upon the received identification data. The determined reputation score is indicative of reputation of the messaging entity. The determined reputation score is used in deciding what action is to be taken with respect to a communication associated with the messaging entity.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS [0001] This application claims priority to and the benefit of U.S. Provisional Application Ser. No. 60 / 625,507 (entitled “Classification of Messaging Entities”) filed on Nov. 5, 2004, of which the entire disclosure (including any and all figures) is incorporated herein by reference. [0002] This application is a continuation-in-part of, and claims priority to and the benefit of, commonly assigned U.S. patent application Ser. No. 10 / 093,553, entitled “SYSTEMS AND METHODS FOR ADAPTIVE MESSAGE INTERROGATION THROUGH MULTIPLE QUEUES,” U.S. patent application Ser. No. 10 / 094,211, entitled “SYSTEMS AND METHODS FOR ENHANCING ELECTRONIC COMMUNICATION SECURITY,” and U.S. patent application Ser. No. 10 / 094,266, entitled “SYSTEMS AND METHODS FOR ANOMALY DETECTION IN PATTERNS OF MONITORED COMMUNICATIONS,” all filed on Mar. 8, 2002, each of which are hereby incorporated by reference in their entirety. This application is also a continuation-in-part of, and c...

AI Technical Summary

Benefits of technology

[0005] Current tools for message sender analysis include IP blacklists (sometimes called real-time blacklists (RBLs)) and IP whitelists (real-time whitelists (RWLs)). Whitelists and blacklists certainly add value to the spam classification process; however, whitelists and blacklists are inherently limited to providing a binary-type (YES/NO) response to each query. In contrast, a reputation system has the ability to express an opinion of a sender in terms of a scalar number in some defined range. Thus, where blacklists and whitelists are limited to “black and white” responses, a reputation system can express “shades of gray” in it

Problems solved by technology

Whitelists and blacklists certainly add value to the spam classification process; however, whitelists and blacklists are inherently limited to providing a binary-type (YES / NO) response to each query.

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