A Neural Network Approach for Misuse and Anomaly Intrusion Detection

摘要

An MI.P(Multi-Layer Perception)/Elman neural network is proposed in this paper, which realizes classification with memory of past events using the real-time classification of MI.P and the memorial functionality of Elman. The system's sensitivity for the memory of past events ean be easily reconfigured without retraining the whole network. This approach can he used for both misuse and anomaly detection system. The intrusion detection systems(TDSs) using the hybrid MLP/Elman neural network are evaluated by the intrusion detection evaluation data sponsored by U.S. Defense Advanced Research Projects Agency CDARPA) Ihc results of experiment are presented in Receiver Operating Characteristic CROC) curves. Thc capabilites of these IDSs to identify Deny ofService(DOS) and probing attacks are enhanced.