ABSTRACT: With the growing diverse demands for Internet applications, network security issues become more acute. To address the appropriate network security from network intrusion detection event has become an important research in network security. In this paper, user behavior features are extracted to create the model for the user transmission behavior. The demands for anomaly detection and the specific characteristics of audit data are studied. An intrusion detection algorithm and based on statistics variance method in user transmission behavior (IDSV) and the implementation framework are provided. And then, the IDSV algorithm is applied into ARP spoofing detection. The simulation results show that IDSV algorithm does well in detection rate of intrusion detection and has good detection performance of different application features. The IDSV algorithm can detect intrusion effectively under user behavior in different applications.
Computational and Information Sciences (ICCIS), 2010 International Conference on; 01/2011