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Bio-inspired, cross-layer protocol design for intrusion detection and identification in wireless sensor networks

机译:生物启发的跨层协议设计,用于无线传感器网络中的入侵检测和识别

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Published studies have focused on the application of one bio-inspired or evolutionary computational method to the functions of a single protocol layer in a wireless ad hoc sensor network (WSN). In a novel departure from previous work, the cross-layer approach to WSN protocol design suggests applying a bio-inspired evolutionary computational method to the functions of each protocol layer to improve the intrusion detection identification (IDID) performance of a WSN cross-layer design beyond that of a single method assigned to only one layer's functions. A cross-layer design, embedding genetic algorithms, anti-phase synchronization, ant colony optimization, and a trust model based on quantized data reputation at the physical (PHY), medium access control (MAC), network, and application layers, respectively, is constructed. Simulation results demonstrate synergies among the bio-inspired methods of the proposed baseline design improve overall IDID performance of networks over that of a single computational method.
机译:已发表的研究集中于将一种生物启发或进化计算方法应用于无线自组织传感器网络(WSN)中单个协议层的功能。与以前的工作有所不同的是,WSN协议设计的跨层方法建议将生物启发式的进化计算方法应用于每个协议层的功能,以提高WSN跨层设计的入侵检测识别(IDID)性能超出了仅分配给一层​​功能的单一方法。分别基于物理层(PHY),介质访问控制(MAC),网络层和应用层的量化数据信誉,进行跨层设计,嵌入遗传算法,反相同步,蚁群优化和信任模型,被建造。仿真结果表明,所提出的基线设计的生物启发方法之间的协同作用比单个计算方法可提高网络的整体IDID性能。

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