Reconfigurable spam detection system based on global intelligence

Abstract

Systems are provided for delaying e-mail classification until global intelligence has an opportunity to be gathered. According to one embodiment, a spam detection system includes a global intelligence network and a network device. The global intelligence network contains global intelligence servers coupled to a public network and configured to (i) gather intelligence from distributed anti-spam engines, (ii) maintain and update e-mail message signatures and associated reputation information and (iii) readjust spam detection characteristics of the distributed anti-spam engines. The network device includes an anti-spam engine, which is configured to (i) perform reputation analysis and content analysis on observed e-mail messages and (ii) provide the global intelligence network with an opportunity to gather further information to make the content analysis more accurate by queuing e-mail messages for which a satisfactory spam or clean categorization cannot be made in real-time for subsequent reapplication of the reputation analysis or the content analysis.

Description

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AI Technical Summary

Benefits of technology

The patent describes a system for detecting spam in email messages. The system uses a global intelligence network to gather intelligence from multiple anti-spam engines and maintains a database of email message signatures and associated reputation information. The system also includes an anti-spam engine that performs analysis on email messages and queues them up for further analysis if there is no definitive categorization in real-time. The technical effect of this system is that it can detect spam more accurately and efficiently by using global intelligence and queuing up additional analysis if needed.

Problems solved by technology

The technical problem addressed in this patent text is the need for improved anti-spam systems and services to effectively deal with the problem of spam and other unwanted bulk messages that can be sent through various means of electronic communication. Existing techniques such as greylisting, greeting delay, and checksum-based filtering have limitations and can result in the loss of valid, non-spam messages. There is a need for new methods and systems that can better identify and prevent spam at its source and protect against the negative impacts of spam on traffic handling mechanisms and computer networks.

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