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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Exploiting Jamming-Caused Neighbor Changes for Jammer Localization
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Exploiting Jamming-Caused Neighbor Changes for Jammer Localization

机译:利用干扰引起的邻居变化进行干扰定位

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Jamming attacks are especially harmful when ensuring the dependability of wireless communication. Finding the position of a jammer will enable the network to actively exploit a wide range of defense strategies. In this paper, we focus on developing mechanisms to localize a jammer by exploiting neighbor changes. We first conduct jamming effect analysis to examine how the communication range alters with the jammer's location and transmission power using free-space model. Then, we show that a node's affected communication range can be estimated purely by examining its neighbor changes caused by jamming attacks and thus, we can perform the jammer location estimation by solving a least-squares (LSQ) problem that exploits the changes of communication range. Compared with our previous iterative-search-based virtual force algorithm, our LSQ-based algorithm exhibits lower computational cost (i.e., one step instead of iterative searches) and higher localization accuracy. Furthermore, we analyze the localization challenges in real systems by building the log-normal shadowing model empirically and devising an adaptive LSQ-based algorithm to address those challenges. The extensive evaluation shows that the adaptive LSQ-based algorithm can effectively estimate the location of the jammer even in a highly complex propagation environment.
机译:在确保无线通信的可靠性时,干扰攻击尤其有害。找到干扰源的位置将使网络能够积极利用各种防御策略。在本文中,我们重点研究通过利用邻居变化来定位干扰器的机制。我们首先进行干扰效果分析,以使用自由空间模型检查通信范围如何随干扰器的位置和发射功率而变化。然后,我们表明,可以纯粹通过检查由干扰攻击引起的邻居变化来估计节点的受影响通信范围,因此,我们可以通过解决利用通信范围变化的最小二乘(LSQ)问题来执行干扰位置估计。与我们以前的基于迭代搜索的虚拟力算法相比,我们基于LSQ的算法显示出较低的计算成本(即以一步代替迭代搜索)和更高的定位精度。此外,我们通过经验建立对数正态阴影模型并设计基于LSQ的自适应算法来解决这些挑战,从而分析实际系统中的定位挑战。广泛的评估表明,即使在高度复杂的传播环境中,基于LSQ的自适应算法也可以有效地估计干扰源的位置。

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