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This paper present Ares, a reverse engineering technique for assisting in the analysis of data recovered for the investigation of mobile and embedded systems. The focus of investigations into insider activity is most often on the data stored on the insider's computers and digital devices - call logs, email messaging, calendar entries, text messages, and browser history - rather than on the status of the system's security. Ares is novel in that it uses a data-driven approach that incorporates natural language processing techniques to infer the layout of input data that has been created according to some unknown specification.
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