A Hybrid Data Mining Based Intrusion Detection System for Wireless Local Area Networks
The exponential growth in wireless network faults, vulnerabilities, and attacks make the WLAN security management a challenging research area. Data mining applied to intrusion detection is an active area of research. The main reason for using data mining techniques for intrusion detection systems is due to the enormous volume of existing and newly appearing network data that require processing. Data mining follows anomaly based intrusion detection. The drawback of the anomaly based intrusion detection in a wireless network is the high rate of false positive. This can be solved by a designing a hybrid intrusion detection system by connecting a misuse detection module to the anomaly detection module.