Bayesian Models Applied to Cyber Security Anomaly Detection Problems
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Nowadays cyber security is an important concern for all individuals, organisations and governments globally. Cyber attacks have become more sophisticated, frequent and more dangerous than ever, and traditional anomaly detection methods have been proven to be less effective when dealing with these new classes of cyber attacks. In order to address this, both classical and Bayesian statistical models offer a valid and innovative alternative to the traditional signature-based methods, motivating the increasing interest in statistical research that it has been observed in recent years. In this review paper we provide a description of some typical cyber security challenges and the kind of data involved, paying special attention to Bayesian approaches for these problems
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