Research on the security audit model in intrusion prevention based on write-related support vector data description - LUO Jun; PAN Zhi-song; MIAO Zhi-min; HU Gu-yu (Tongxin xuebao)
The security audit model based on write-related SVDD was designed to resolve the one-class problem.Once the classifier has been trained using the write-related subset,all activities deviated from the normal patterns are classified as potential intrusion.The proposed one-class classification algorithms can be implemented to build up an anomaly detection system by using only normal samples and the algorithms also makes the security audit system detect the new anomaly behaviors.In the experiments,the One-class classifier acquires nearly 100% detection rate and average zero false alarm rate for sequences of system calls based on a small training dataset.