Spam is a massive problem - it currently accounts for between 1/3 and 1/2 of all emails and costs companies billions of dollars as the result of lower productivity, loss of legitimate messages and the need for increased bandwidth and storage. In a bid to try solve the problem, IBM has brought together scientists from different areas of research division to develop an enterprise anti-spam filtering system which combines several different filtering technologies to create the ultimate anti-spam system. For example one of the spam filters - Chung-Kwei - is a pattern-discovery-based system which uses an algorithm developed by life sciences researchers focused tackling computational biology challenges such as gene finding and protein annotation. By itself, Chung-Kwei detected 96.56 percent of spam messages with just a .066 percent false positive rate during tests conducted in IBM’s labs. By combining Chung-Kwei with the other spam filtering techniques, IBM researchers have created SpamGuru - a prototype anti-spam system which they believe has the potential to eliminate virtually all spam.
SpamGuru: An Enterprise Anti-Spam Filtering System
IBM Research is developing an enterprise-class anti-spam filter as part of our overall strategy of attacking the Spam problem on multiple fronts. Our anti-spam filter, SpamGuru, mirrors this philosophy by incorporating several different filtering technologies and intelligently combining their output to produce a single spamminess rating or score for each incoming message. The use of multiple algorithms improves the system’s effectiveness and makes it more difficult for spammers to attack. While a spammer may defeat any single algorithm, SpamGuru can rely on its remaining algorithms to maintain a high-degree of effectiveness.
Christine Paulus | IBM
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