Methods and systems for detecting and preventing the spread of malware on instant messaging (im) networks by using bayesian filtering

Abstract

Methods and systems for reducing the spread of malware in communication between an instant message (IM) client and an IM server are described. An IM filter module (IM FM) is configured to analyze messages exchanged between an IM server and an IM client. The IM FM also identifies one or more messages as possibly containing malware among the exchanged messages and assigns a confidence level to each identified message. A confidence level represents a probability of a message containing malware. A Bayesian filter is configured to train itself using the identified messages and the confidence levels and adjust the confidence levels. A feedback training mechanism for the Bayesian filter is also included. In particular, the IM FM examines additional messages exchanged between the IM server and IM client, identifies one or more messages as possibly containing malware among the additional messages using the adjusted confidence values. The IM FM also assigns a confidence level to each additionally identified message. The Bayesian filter is further configured to re-train itself using the identified messages, the additionally identified messages, and the confidence levels and adjust the confidence levels.