Identifying malware using cross-evidence correlation

Abstract

This paper proposes a new correlation method for the automatic identification of malware traces across multiple computers. The method supports forensic investigations by efficiently identifying patterns in large, complex datasets using link mining techniques. Digital forensic processes are followed to ensure evidence integrity and chain of custody.