Detection Of Black Hole Attacks in Mobile Ad Hoc Networks: A Comprehensive Literature Review

Abstract

Mobile Ad Hoc Networks (MANETs) represent a critical infrastructure-less networking paradigm where mobile nodes communicate wirelessly without centralized administration. However, their inherent characteristics—dynamic topology, open medium, distributed cooperation, and lack of fixed infrastructure—make them particularly vulnerable to security threats. Among these, the black hole attack stands out as one of the most severe routing layer attacks, where malicious nodes falsely advertise optimal routes to destinations, intercept data packets, and subsequently drop them instead of forwarding, severely degrading network performance.

This comprehensive literature review examines the state-of-the-art research on black hole attack detection in MANETs, synthesizing findings from 30 highly relevant peer-reviewed publications spanning 2012 to 2025. The review systematically analyzes detection methodologies, key findings, performance metrics, and persistent challenges in this domain. Major detection approaches include routing protocol modifications, trust-based mechanisms, cryptographic techniques, machine learning-based anomaly detection, and intrusion detection systems. Research demonstrates that effective detection mechanisms can significantly improve packet delivery ratios (from 30% to over 90%), reduce end-to-end delays, and enhance overall network security. However, challenges persist regarding computational overhead, scalability, false positive rates, and detection of sophisticated cooperative and smart black hole attacks. This review provides researchers and practitioners with a structured understanding of current capabilities, limitations, and future research directions in securing MANETs against black hole attacks.