An evaluation of connection characteristics for separating network attacks
International Journal of Security and Networks
A reliable context-aware intrusion tolerant system
OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems - Volume Part II
On RSN-oriented wireless intrusion detection
OTM'07 Proceedings of the 2007 OTM confederated international conference on On the move to meaningful internet systems: CoopIS, DOA, ODBASE, GADA, and IS - Volume Part II
Wireless intrusion detection based on different clustering approaches
Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India
WiFi miner: an online apriori-infrequent based wireless intrusion system
Sensor-KDD'08 Proceedings of the Second international conference on Knowledge Discovery from Sensor Data
A survey of intrusion detection techniques for cyber-physical systems
ACM Computing Surveys (CSUR)
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Intrusion detection in wireless networks has become an indispensable component of any useful wireless networksecurity systems, and has recently gained attention in both research and industry communities due to widespread use of Wireless Local Area Networks (WLANs). This paper focuses on detecting intrusions or anomalous behaviors in WLANs with data clustering techniques. We first explore the security vulnerabilities of 802.11 or WI-FI networks and summarize the network traffic metrics that are important to model the security of wireless networks. Based on the metric studied we propose a clustering-based intrusion detection approach and evaluate it on a real-world large wireless network traffic dataset. The evaluation results demonstrate the eflectiveness of our proposed intrusion detection approach for wireless networks.