to the problems higher rate of false retrieval in anomaly detection system due to the uncertainty of intrusion, this paper presents an anomaly detection model based on q- learning algorithm (qladm).
针对网络入侵的不确定性导致异常检测系统误报率较高的不足,提出一种基于q-学习算法的异常检测模型(qladm)。该模型把q-学习、行为意图跟蹤和入侵预测结合起来,可获得未知入侵行为的检测和响应。