Support vector machines for spam categorization
IEEE Transactions on Neural Networks
Spam attacks: p2p to the rescue
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Collision Module Integration in a Specific Graphic Engine for Terrain Visualization
IV '04 Proceedings of the Information Visualisation, Eighth International Conference
Collaborative spam filtering with heterogeneous agents
Expert Systems with Applications: An International Journal
A survey of emerging approaches to spam filtering
ACM Computing Surveys (CSUR)
Immune-Based peer-to-peer model for anti-spam
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
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With the growing amount of internet users, a negative form of sending email spreads that affects more and more users of email accounts: Spamming. Spamming means that the electronic mailbox is congested with unwanted advertising or personal email. Sorting out this email costs the user time and money. This paper introduces a distributed spam filter, which combines an off-the-shelf text classification with multiagent systems. Both the text classification as well as the multiagent platform are implemented in Java. The content of the emails is analyzed by the classification algorithm 'support vector machines'. Information about spam is exchanged between the agents through the network. Identification numbers for emails which where identified as spam are generated and forwarded to all other agents connected to the network. These numbers allow agents to identify incoming spam email. In this way, the quality of the filter increases continuously.