遗传算法与模糊理论结合的传感网络防御算法

WIRELESS SENSOR NETWORK DEFENSE ALGORITHM BASED ON GENETIC ALGORITHM AND FUZZY THEORY

  • 摘要: 由于无线传感器网络(WSNs)的通信链路并不如有线网络一样私密可控,在面对伪装认可攻击(FEIAs)时鲁棒性不强。针对这种情况,提出基于遗传算法与模糊理论的自适应防御(ACS)方案。针对ACS方案容易对FEIAs产生误判的问题,重点分析了安全参数选择,并对此方案进行模拟仿真。仿真结果显示提出的结合型防御算法相较于传统ACS方案减少了存储需求和计算复杂度,能提高检测精度,同时能在单一WSN模型中有效实现,实现模糊系统的自适应优化。

     

    Abstract: The communication link of wireless sensor networks (WSNs) is not as private and controllable as wired network, and its robustness is not strong in the face of false endorsement insertion attacks (FEIAs). In view of this, this paper combines the genetic algorithm and fuzzy theory, and proposes an adaptive defense scheme (ACS). Aiming at the problem that ACS scheme was prone to misjudge FEIAs, this paper focused on the selection of safety parameters. And this scheme was simulated. The simulation results show that compared with the traditional ACS scheme, the combined defense algorithm reduces the storage requirements and computational complexity, improves the detection accuracy, and can be effectively implemented by a single WSN model, so as to realize the adaptive optimization of fuzzy system.

     

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