Semantic Analysis for Monitoring Insider Threats

Malicious insiders’ difficult-to-detect activities pose serious threats to the intelligence community (IC) when these activities go undetected. A novel approach that integrates the results of social network analysis, role-based access monitoring, and semantic analysis of insiders’ communications as evidence for evaluation by a risk assessor is being tested on an IC simulation. A semantic analysis, by our proven Natural Language Processing (NLP) system, of the insider’s text-based communications produces conceptual representations that are clustered and compared on the expected vs. observed scope. The determined risk level produces an input to a risk analysis algorithm that is merged with outputs from the system’s social network analysis and role-based monitoring modules.

• Type: Conference
• Year: 2004
• Where: ISI
• Authors: Svetlana Symonenko, Elizabeth D. Liddy, Ozgur Yilmazel, Robert Del Zoppo, Eric Brown, Matt Downey
• Keywords: ISI 2004, Role-based Access Monitoring, Semantic Analysis, Social Network Analysis