A Novel Intrusion Detection System for Mitigating Black Hole Attacks in Wireless Networks

Abstract

This study introduces an innovative Intrusion Detection System (IDS) designed to mitigate black hole attacks in wireless networks, particularly in the context of the NS2 simulation platform. Black hole attacks, wherein malicious nodes deliberately drop or misroute data packets, severely disrupt network reliability and connectivity. Traditional security measures, including encryption and authentication, are insufficient against such threats. The proposed IDS integrates anomaly detection with signature-based techniques, enabling the identification of both known and novel black hole attack patterns. The system employs adaptive learning, allowing continuous enhancement of detection accuracy by analysing past network behaviours and evolving threats. Extensive simulations using the AODV routing protocol on the NS2 platform validate the system's efficiency in maintaining network integrity and performance. This IDS provides a robust Défense mechanism for wireless networks, ensuring secure and reliable communication, particularly for critical applications in IoT, smart city infrastructure, and military domains.