Multiple Spoofing Adversaries Detection and Localization in Wireless Networks

The openness of wireless networks enables adversaries to deception as other devices. Spoofing attacks are vulnerable in wireless network, which are allowed the many form of attacks in the network. Wireless spoofing attacks are effortless to start and can extensively impact the performance of networks. A physical property coupled with each node is proposed which uses spatial information, hard to forge, and not contingent on cryptography, as the beginning for, detecting spoofing attacks, determining the number of attackers when multiple adversaries hidden as the same node identity and localizing multiple adversaries. To use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. An integrated detection and localization system is developed to localize the positions of multiple attackers.