User and entity behavior analytics for enterprise security
This paper presents an overview of an intelligence platform we have built to address threat hunting and incident investigation use cases in the cyber security domain. Specifically, we focus on User and Entity Behavior Analytics (UEBA) modules that track and monitor behaviors of users, IP addresses and devices in an enterprise. Anomalous behavior is automatically detected using machine learning algorithms based on Singular Values Decomposition (SVD) Such anomalous behavior indicative of potentially malicious activity is alerted to analysts with relevant contextual information for further investigation and action. We provide a detailed description of the models, algorithms and implementation underlying the module and demonstrate the functionality with empirical examples.
2016 IEEE International Conference on Big Data (Big Data)