关键词: 反馈神经网络, 入侵检测, 异常检测

Abstract:

Current intrusion detection systems lack the ability to generalize from previously observed attacks and to detect even slight variations of known attacks. An approach employing LS and neural networks was described to provide the ability to generalize from previously observed behavior and to recognize future unseen behavior. The method was represented to use feedback neural networks in anomaly detection to structure the characteristic pattern of the short sequences of system calls. Meanwhile, the algorithm and design of the neural network were given. Experiment shows that the neural network is especially better to deal with events and variance of intrusions and improves the detection rate without increasing the false positives.

Key words: feedback neural network, intrusion detection, anomaly detection