A Customizable Ranking Method for Digital Evidence Search through Interestingness Injection

Digital evidence search is one of the key issues in digital forensics. Current forensic search tools just present the results without a kind of grouping or inappropriate filtering. So a criminal investigator has to spend a lot of time in order to find documents related to the investigation among the searched results. If the interestingness of the crime investigator is injected into the system, the system can rank the search hits according to it and present the most relevant results to him. In this paper we present a customizable ranking method through injecting the interestingness of crime investigator to improve the performance of digital evidence search in email forensics.