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

机译:基于距离的无线网络中多个欺骗攻击者的检测和定位

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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.
机译:无线网络易于遭受基于身份的欺骗攻击,并且往往会降低网络性能。接收信号强度(RSS)空间相关通常用于检测和定位欺骗攻击。这不适用于RSS值不稳定且随距离变化的环境。对于多个对手的准确定位,这种方法也是不理想的。本文提出了一种基于距离的检测与定位(DDL)算法,该算法将距离参数添加到现有系统中,以进行欺骗检测和对多个对手的精确定位。此外,它可以确定攻击者的数量,将其从网络中消除,从而提高网络性能。仿真结果表明,这项提议的工作提供了出色的本地化性能,并且在包括IEEE 802.11(WiFi)和IEEE 802.15.4(ZigBee)网络在内的不同技术中通用。

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