Abstract
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.
Highlights
Wireless sensor network (WSN) is widely used in many applications such as industrial monitoring, environmental monitoring, forest monitoring, health care, and military. e architecture of WSN is categorized into clustered and flat [1]
Results and Discussion e performance of layer trust-based intrusion detection system (LB-IDS) is evaluated by comparing the results of the three performance metrics such as detection accuracy, false-positive rate (FPR), and false-negative rate (FNR) with the results of Wang’s scheme
FPR and FNR calculate at what ratio the detection accuracy is true or false. e computer simulations are performed using MATLAB R2015a. e machine in which the simulation is performed has 6 Gb RAM, core i7 processor, and Windows 10 platform. e LB-IDS scheme is compared with the most recent Wang et al [1] scheme, which is based on protocol layer trust
Summary
WSN is widely used in many applications such as industrial monitoring, environmental monitoring, forest monitoring, health care, and military. e architecture of WSN is categorized into clustered and flat [1]. E authors proposed an IDS for WSN using trust-based system In this model, a trust is separately calculated for each SN at the physical layer, MAC layer, and network layer using trust metrics. In [1], at the physical layer, energy consumption is considered as the trust metric for the trust value calculation. At the MAC layer, back-off time is considered as the trust metric for the trust value calculation. The number of hops advertised is considered as the trust metric for the trust value calculation. (1) LB-IDS is proposed to detect the malicious nodes in the clustered WSN In this method, a trust value of an SN is individually calculated at the physical layer, MAC layer, and network layer using the deviation of trust metrics.
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