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Over the past few years, the number of crimes related to the worldwide diffusion of digital devices with large storage and broadband network connections has increased dramatically. In order to better address the problem, law enforcement specialists have developed new ideas and methods for retrieving evidence more effectively. In accordance with this trend, our research aims to add new pieces of information to the automated analysis of evidence according to Machine Learning-based “post mortem” triage. The scope consists of some copyright infringement court cases coming from the Italian Cybercrime Police Unit database. We draw our inspiration from this “low level” crime which is normally sat at the bottom of the forensic analyst's queue, behind higher priority cases and dealt with the lowest priority. The present work aims to bring order back in the analyst's queue by providing a method to rank each queued …