关键词: 入侵检测, 异常检测, D-S证据理论, 支持向量机（SVM）

Abstract: Intrusion detection is the indispensable part of computer network security, and anomaly detection system is hot in this research field. One of the existing detection methods, SVM maintains good condition of small-scale dataset. But the single SVM detection still exists the limitation that low rate of detection and high rate of false positives. Combined with evidential theory, it puts forward an anomaly detection method based on SVM fusion, effectively covers the limitation of the single SVM detection. Evaluation data profiling KDD99 experiments shows that this method increases the intrusion detection rate while reducing false positives, greatly improves the detection performance of the intrusion detection system.

Key words: intrusion detection, anomaly detection, Dempster-Shafer theory, Support Vector Machine（SVM）