Network Traffic Anomaly Detection Using Recurrent Neural Networks

28 Mar 2018Benjamin J. RadfordLeonardo M. ApolonioAntonio J. TriasJim A. Simpson

We show that a recurrent neural network is able to learn a model to represent sequences of communications between computers on a network and can be used to identify outlier network traffic. Defending computer networks is a challenging problem and is typically addressed by manually identifying known malicious actor behavior and then specifying rules to recognize such behavior in network communications... (read more)

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