A meta data mining framework for botnet analysis

Botnets are a group of compromised computers that act in a coordinated manner against a target determined by a single point of control. Meta-analysis of botnets is crucial as it results in knowledge about the botnet, often providing valuable information to researchers who are looking to eradicate it. However, meta-analysis has not been applied from a research standpoint for botnets detection and analysis. This paper proposes a framework that uses modified implementation of Apriori data mining algorithms on data-sets derived from end-user logs for meta-analysis. It also presents a case study following the proposed approach. The results of this case study present some interesting heuristics that can be used to eradicate the botnet. These heuristics include the indication of vulnerabilities, new trends in botnet malware among others.