Developing a Hybrid Detection Approach to Mitigating Black Hole and Gray Hole Attacks in Mobile Ad Hoc Networks

Abstract

Mobile ad hoc networks (MANETs) have revolutionized wireless communications by enabling dynamic, infrastructure-free connectivity across various applications, from disaster recovery to military operations. However, these networks are highly vulnerable to security threats, particularly black hole and gray hole attacks, which can severely disrupt network performance and reliability. This study addresses the critical challenge of detecting and mitigating these attacks within the framework of the dynamic source routing (DSR) protocol. To tackle this issue, we propose a robust hybrid detection method that significantly enhances the identification and mitigation of black hole and gray hole attacks. Our approach integrates anomaly detection, advanced data mining techniques, and cryptographic verification to establish a multi-layered defense mechanism. Extensive simulations demonstrate that the proposed hybrid method achieves superior detection accuracy, reduces false positives, and maintains high packet delivery ratios even under attack conditions. Compared to existing solutions, this method provides more reliable and resilient network performance, dynamically adapting to evolving threats. This research represents a significant advancement in MANET security, offering a scalable and effective solution for safeguarding critical MANET applications against sophisticated cyber-attacks.

Keywords

• hybrid detection
• black hole attacks
• gray hole attacks
• mobile ad hoc networks