robincamille + thesisanon   17

Cyber Security and Information Systems Information Analysis Center
Determining an IM user’s real identity relies on the fact that humans are creatures of habit and have certain persistent personal traits and patterns of behavior, known as behavioral biometrics (Revett, 2008). Online writing habits, known as stylometric features, include composition syntax and layout, vocabulary patterns, unique language usage, and other stylistic traits. Thus, certain stylometric features may be used to create an author writeprint to help identify an author of a particular piece of work (De Vel et al., 2001).
february 2016 by robincamille
Dark Web and GeoPolitical Web Research | Artificial Intelligence Laboratory
Authorship analysis and Writeprint
Grounded in authorship analysis research, we have developed the (cyber) Writeprint technique to uniquely identify anonymous senders based on the signatures associated with their forum messages. We expand the lexical and syntactic features of traditional authorship analysis to include system (e.g., font size, color, web links) and semantic (e.g., violence. racism) features of relevance to online texts of extremists and terrorists. We have also developed advanced Inkblob and Writeprint visualizations to help visually identify web signatures. Our Writeprint technique has been developed for Arabic, English, and Chinese languages. The Arabic Writeprint consists of more than 400 features, all automatically extracted from online messages using computer programs. Writeprint can achieve an accuracy level of 95%.
february 2016 by robincamille

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