Efficient Accurate Context-Sensitive Anomaly Detection

For program behavior-based anomaly detection, the only way to ensure accurate monitoring is to construct an efficient and precise program behavior model. A new program behavior-based anomaly detection model,called combined pushdown automaton (CPDA) model was proposed, which is based on static binary executable analysis. The CPDA model incorporates the optimized call stack walk and code instrumentation technique to gain complete context information. Thereby the proposed method can detect more attacks, while retaining good performance.