An Algorithmic Framework for Sinkhole Attack Detection and Mitigation in Wireless Sensor Networks
Aina Mehta, Jasminder Kaur Sandhu · 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · 2022
These sensor networks have become more pervasive nowadays, as they surround us also in the everyday daily environment; due to which security and privacy become a major concern. Moreover, these sensor nodes are distributed in remote areas of the network due to which they get suspectable to security threats leading to exploitation of functioning of the network. The main objective is to ensure robust applications in the presence of attackers. These malicious attackers try to intrude in the network so that they can access sensitive data or spread false information through the network. Therefore, it becomes mandatory to detect these attacks effectively on all layers of the network model, but mainly the attack on the network layer i.e., sinkhole. In this paper, we focus on one such attack called sink hole attack in which malicious node assumes its shortest path to sink. This paper proposes a new technique SDSN (Severity Detection of Sinkhole Attack) for detection and RHSN (Removal of Highest Severity Node) for mitigating the node. Proposed technique is implemented in NS2 and extensive simulations are performed to obtain the results. Results indicate the superiority of the proposed approach over existing approaches in terms of (packet loss, energy consumption, delay and throughput).