Layering of edge node for jamming attack detection and elimination in wireless sensor network

Abstract

SummaryWireless sensor network (WSN) is an environmental monitoring system exposing sensor nodes to various attacks. Jamming is an attack that disrupts the entire sensor network and affects the network's life span. The jammer broadcasts the signal at a frequency similar to the broadcast signal to jam the corresponding sensor node. There are many jamming detection schemes that only detect the jamming node, but they do not focus on eliminating the node that is not jamming. In this article, a novel strategy is used along with optimization to eliminate the disturbance in the sensor network and save the power consumed by nodes. The system uses the edge node, the sub‐edge node, and the cluster head for detection of jamming attack. Hyperbolic optimization is implemented in the cluster to eliminate data transmission failures. The proposed model considers the node's round trip time to detect jamming attacks. The optimization method considers the cluster head as the cluster member based on the probability of jamming in the network. The design is implemented and analyzed in MATLAB platform. As a result, the proposed method has improved the detection accuracy to 11.1% compared with extant techniques.

Clustering-Based Energy-Efficient Self-Healing Strategy for WSNs under Jamming Attacks

“…However, the problem of authentication in the context of the cluster with a focus on energy efficiency is only considered in [ 31 ]. In [ 33 ], jamming is considered in a specific clustering context. The work proposes a novel strategy that aims to detect and eliminate the jammer node present in the network to improve energy efficiency.…”

“…Only the method proposed here addresses jamming with a multidimensional perspective, exploring clusters to efficiently control the transmit power, to self-heal and to maintain persistent operation despite the presence of jamming. ---Armor-LEACH [15] ---MS-LEACH [16] ---SEC [17] ---Enhanced SLEACH [19] ---Maheshwari [22] ---Behera [23] ----Alazab [25] ----Sundararaj [31] ----Murugaveni [33] --Bordon [34] ----Yabcznski [35] ---Fascista [36] ----Just [37] ----Nazib [38] ----Almasoud [39] --Li [40] ---Our Proposal…”

Artificial Neural Network-Based Mechanism to Detect Security Threats in Wireless Sensor Networks

“…A hybrid spectrum management optimization (HSMO) technique was proposed in [ 18 ] for identifying and resolving jammed nodes within a network. This method involves the utilization of edge nodes, sub-edge nodes, and cluster heads to detect and address jammed nodes.…”