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A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang
A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang
Research & Publications
The Cloud Security Alliance lists data theft and insider attacks as critical threats to cloud security. Our work puts forth an approach using a train, monitor, detect pattern which leverages a stateful rule based k-nearest neighbors anomaly detection technique and system state data to detect inside attacker data theft on Infrastructure as a Service (IaaS) nodes. We posit, instantiate, and demonstrate our approach using the Eucalyptus cloud computing infrastructure where we observe a 100 percent detection rate for abnormal login events and data copies to outside systems.