Anomaly-based protection approach against wireless network attacks

The increasing deployment of Wireless Networks has experienced also an exponential increase in wireless faults vulnerabilities and attacks. In this paper, we present a wireless self-protection system (WSPS) that has the following significant features: online monitor of the behavior of wireless network, generate relevant network features, track wireless network state machine violations, generate wireless flow keys (WFK), and use the dynamically updated anomaly and misuse rules to detect complex known and unknown wireless attacks. WSPS quantifies the attack impact using the abnormality distance from the baseline normal models. We validate the WSPS approach by experimenting with different wireless attacks, and show that WSPS can detect accurately wireless network attacks and proactively protect against these attacks.