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A Novel Method of Inconsistent Collision Detection to Prevent Cloning Attacks in High-Security Wireless Body Area Networks

机译:防止高安全性无线人体局域网中克隆攻击的不一致冲突检测新方法

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Remote monitoring of physiological data of patient is emerging as technology called Wireless Body Area Networks (WBAN). As WBAN devices are operated in hostile environments, providing security and privacy to patients are challenging tasks. Due to simple, low cost and resource constrained nature of the sensors of WBAN, adversary can easily compromise one or more nodes and make clones of compromised nodes to launch different insider attacks in the network. In this paper, we propose a clone detection and prevention strategy for WBAN by leveraging inconsistent collisions so that legitimate nodes of WBAN are alone allowed to participate in communication, while preventing the cloned nodes. Through simulation, we show that the proposed algorithm can detect cloning attack fairly fast and with required accuracy under various conditions.
机译:远程监测患者的生理数据作为一种称为无线人体局域网(WBAN)的技术正在兴起。由于WBAN设备在恶劣的环境中运行,因此为患者提供安全性和隐私性是一项艰巨的任务。由于WBAN传感器的简单,低成本和资源受限的性质,对手可以轻松地破坏一个或多个节点,并克隆受感染节点,从而在网络中发起不同的内部攻击。在本文中,我们通过利用不一致的冲突提出了WBAN的克隆检测和预防策略,以便仅允许WBAN的合法节点参与通信,同时防止克隆节点。通过仿真,我们证明了该算法可以在各种条件下相当快地以所需的精度检测克隆攻击。

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