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LB-IDS: Securing Wireless Sensor Network Using Protocol Layer Trust-Based Intrusion Detection System

机译:LB-ID:使用基于协议层信任的入侵检测系统来保护无线传感器网络

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Wireless sensor network (WSN) faces severe security problems due to wireless communication between the nodes and open deployment of the nodes. The attacker disrupts the security parameters by launching attacks at different layers of the WSN. In this paper, a protocol layer trust-based intrusion detection system (LB-IDS) is proposed to secure the WSN by detecting the attackers at different layers. The trust value of a sensor node is calculated using the deviation of trust metrics at each layer with respect to the attacks. Mainly, we consider trustworthiness in the three layers such as physical layer trust, media access control (MAC) layer trust, and network layer trust. The trust of a sensor node at a particular layer is calculated by taking key trust metrics of that layer. Finally, the overall trust value of the sensor node is estimated by combining the individual trust values of each layer. By applying the trust threshold, a sensor node is detected as trusted or malicious. The performance of LB-IDS is evaluated by comparing the results of the three performance parameters such as detection accuracy, false-positive rate, and false-negative rate, with the results of Wang’s scheme. We have implemented jamming attack at the physical layer, back-off manipulation attack at the MAC layer, and sinkhole attack at the network layer using simulations. We have also implemented a cross-layer attack using the simulation where an attacker simultaneously attacks the MAC layer and network layer. Simulation results show that the proposed LB-IDS performs better as compared with Wang’s scheme.
机译:无线传感器网络(WSN)由于节点之间的无线通信和节点的开放部署而面临严重的安全问题。攻击者通过在WSN的不同层发射攻击来扰乱安全参数。在本文中,提出了一种基于协议层信任的入侵检测系统(LB-ID)来通过检测不同层的攻击者来保护WSN。使用每个层的信任度量相对于攻击来计算传感器节点的信任值。主要是,我们认为,在三层之类的诸如物理层信任,媒体访问控制(MAC)层信任和网络层信任之类的三层中的可信度。通过考虑该层的关键信任度量来计算特定层处的传感器节点的信任。最后,通过组合每个层的各个信任值来估计传感器节点的整体信任值。通过应用信任阈值,将传感器节点被检测为可信或恶意。通过比较三种性能参数的结果,例如检测精度,假阳性率和假负率,以及王’ s计划的结果来评估LB-ID的性能。我们已经在物理层,在MAC层的退避操作攻击处实现了干扰攻击,并使用模拟在网络层处陷入困境。我们还使用攻击者同时攻击MAC层和网络层的仿真来实现跨层攻击。仿真结果表明,与王’ s计划相比,所提出的LB-ID表现更好。

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