The field of digital forensics is faced with a number of challenges, given the constant growth in technologies. The reliability and integrity associated with digital evidence from disparate sources is also a perpetual challenge, requiring considerable human interpretation in the reconstruction of any particular sequence of events. In this paper we present a framework for an integrity-aware Forensic Evidence Management System (FEMS). In an effort to automatethe analysis process, this system would provide investigators with a holistic view of the forensic evidence at hand; thereby providing insights into the quality of investigative inferences. The Biba integrity model is incorporated to preserve the integrity of digital evidence, while Casey’s Certainty Scale is chosen as the integrity classification scheme. A finite state automaton (FSA) is used to model the behaviour of the FEMS. In so doing, cyber crime profiling is achieved.