Anomaly Detection in a Digital Video Broadcasting System Using Timed Automata

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May 24, 2017
Xiaoran Liu, Qin Lin, Sicco Verwer, Dmitri Jarnikov
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This paper focuses on detecting anomalies in a digital video broadcasting (DVB) system from providers' perspective. We learn a probabilistic deterministic real timed automaton profiling benign behavior of encryption control in the DVB control access system. This profile is used as a one-class classifier. Anomalous items in a testing sequence are detected when the sequence is not accepted by the learned model.

* This paper has been accepted by the Thirty-Second Annual ACM/IEEE Symposium on Logic in Computer Science (LICS) Workshop on Learning and Automata (LearnAut)  
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