A collaborative and multi-agent system for e-mail filtering and classification

CAFE (collaborative agents for filtering e-mails) is a multi-agent system to collaboratively filter spam and classify legitimate messages in users´ mail stream. CAFE associates a proxy agent with each user, and this agent represents a sort of interface between the user´s e-mail client and the e-mail server. With the support of other types of agents, the proxy agent makes a classification of new messages into three categories: ham (good messages), spam and spam-presumed. Ham messages can be in their turn divided on the basis of the sender´s identity and reputation. The reputation is collaboratively inferred from users´ ratings. The filtering process is performed using three kinds of approach: a first approach based on the usage of an hash function, a static approach using DNSBL (DNS-based black lists) databases and a dynamic approach based on a Bayesian filter. We give a mathematical representation of the system, showing that if users collaborate, the fault probability decreases in proportion to the number of active users