You scratch my back and i'll scratch yours: combating email overload collaboratively
CHI '09 Extended Abstracts on Human Factors in Computing Systems
A survey of learning-based techniques of email spam filtering
Artificial Intelligence Review
Symbiotic filtering for spam email detection
Expert Systems with Applications: An International Journal
A survey of emerging approaches to spam filtering
ACM Computing Surveys (CSUR)
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Leveraging social networks in computer systems can be effective in dealing with a number of trust and security issues. Spam is one such issue where the "wisdom of crowds" can be harnessed by mining the collective knowledge of ordinary individuals. In this paper, we present a mechanism through which members of a virtual community can exchange information to combat spam. Previous attempts at collaborative spam filtering have concentrated on digest-based indexing techniques to share digests or fingerprints of emails that are known to be spam. We take a different approach and allow users to share their spam filters instead, thus dramatically reducing the amount of traffic generated in the network. The resultant diversity in the filters and cooperation in a community allows it to respond to spam in an autonomic fashion. As a test case for exchanging filters we use the popular SpamAssassin spam filtering software and show that exchanging spam filters provides an alternative method to improve spam filtering performance.