AI-Based Wormhole Attack Detection Techniques in Wireless Sensor Networks

Abstract

The popularity of wireless sensor networks for establishing different communication systems is increasing daily. A wireless network consists of sensors prone to various security threats. These sensor nodes make a wireless network vulnerable to denial-of-service attacks. One of them is a wormhole attack that uses a low latency link between two malicious sensor nodes and affects the routing paths of the entire network. This attack is brutal as it is resistant to many cryptographic schemes and hard to observe within the network. This paper provides a comprehensive review of the literature on the subject of the detection and mitigation of wormhole attacks in wireless sensor networks. The existing surveys are also explored to find gaps in the literature. Several existing schemes based on different methods are also evaluated critically in terms of throughput, detection rate, low energy consumption, packet delivery ratio, and end-to-end delay. As artificial intelligence and machine learning have massive potential for the efficient management of sensor networks, this paper provides AI- and ML-based schemes as optimal solutions for the identified state-of-the-art problems in wormhole attack detection. As per the author’s knowledge, this is the first in-depth review of AI- and ML-based techniques in wireless sensor networks for wormhole attack detection. Finally, our paper explored the open research challenges for detecting and mitigating wormhole attacks in wireless networks.

An optimized crypto‐based routing protocol for secure routing in wireless sensor networks

“…Hanif 26 proposed a model for identifying and mitigating wormhole attacks in the WSN environment. These methods are based on AI and ML for detecting wormhole attacks in WSNs.…”

A Situation Based Predictive Approach for Cybersecurity Intrusion Detection and Prevention Using Machine Learning and Deep Learning Algorithms in Wireless Sensor Networks of Industry 4.0

“…The development of a comprehensive predictive framework for cybersecurity intrusion detection and prevention with a feature of intelligent prioritized is the significant requirement in this context [6]. WSNs are essential communication components for real-time data transfer because to the convergence of digital technologies, however, they are also susceptible to cyberattacks [23], [31]. The understanding of the vital role these networks play in the operation of contemporary enterprises serves as the driving force.…”

“…The performance of these networks is impacted by problems with signal interference and dependability in intricate industrial environments. The use of batterypowered sensors raises additional concerns because prolonged battery life and energy efficiency must be balanced for consistent and dependable operation [23]. Despite security challenges, WSNs are essential to the operation of Industry 4.0's data-driven, networked infrastructure.…”

An adaptive technique for wormhole attack detection in MANET using quantized ad-hoc on-demand multipath distance vector routing protocol

“…Hanif et al 28 review a number of techniques, some of which detect wormhole attacks and others of which offer wormhole attack mitigation. Such methods include RTT and hop count, statistical method and AODV-based neighbour discovery and path selection, cloud, and mobile agent-based methods.…”