Distance based Detection and Localization of multiple spoofing attackers for wireless networks

Abstract

Wireless networks are prone to identity based spoofing attacks and tend to degrade network performance. Received Signal Strength (RSS) spatial correlation is usually used for detecting and localizing spoofing attacks. This cannot be applied to environments where RSS value is not stable and varies with distance. This approach is also not desirable for accurate localization of multiple adversaries. This paper proposes Distance based Detection and Localization (DDL) algorithm that adds distance parameter to the existing system to perform spoofing detection and accurate localization of multiple adversaries. In addition, it determines the number of attackers, eliminates them from the network and thereby improves network performance. Simulation results demonstrate that this proposed work provides excellent localization performance and is generic across different technologies including IEEE 802.11 (WiFi) and IEEE 802.15.4 (ZigBee) networks.