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A Probabilistic Framework for Distributed Localization of Attackers in MANETs

机译:MANET中攻击者的分布式本地化的概率框架

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Mobile Ad-hoc Networks (MANETs) are frequently exposed to a wide range of cyber threats due to their unique characteristics. The lack of a centralized monitoring and management infrastructure and the dynamic nature of their topology pose new and interesting challenges for the design of effective security mechanisms. While conventional methods primarily focus on detecting attacks, in this work we focus on estimating the attackers' physical location in the network, and propose a probabilistic framework for aggregating information gathered from nodes reporting malicious activity in their vicinity. In order to overcome the limitations of the decentralized nature of MANETs, we present a distributed approach to attacker localization based on dynamically partitioning the network into clusters. These self-organizing clusters can (i) independently find the approximate location of the attackers in real time, and (ii) deploy trusted resources to capture attackers. We show, through experiments in a simulated environment, that our approach is effective and efficient.
机译:移动自组织网络(MANET)由于其独特的特性,经常会遭受各种各样的网络威胁。缺乏集中的监视和管理基础结构以及其拓扑结构的动态性质,对设计有效的安全机制提出了新的有趣的挑战。尽管常规方法主要集中于检测攻击,但在这项工作中,我们集中于估计攻击者在网络中的物理位置,并提出了一种概率框架,用于汇总从报告其附近恶意活动的节点收集的信息。为了克服MANET分散性的局限性,我们提出了一种基于将网络动态划分为群集的分布式攻击者定位方法。这些自组织群集可以(i)实时独立地找到攻击者的大概位置,并且(ii)部署可信任的资源来捕获攻击者。通过在模拟环境中进行的实验,我们证明了我们的方法是有效且高效的。

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