A hybrid metaheuristic approach to optimize intrusion detection and malicious node identification in mobile Ad Hoc networks

An Intrusion Detection System (IDS) is a vital security mechanism that monitors network or system activities to detect and mitigate malicious behaviors. By identifying threats such as unauthorized access or sabotage, the IDS responds promptly to prevent further compromise, ensuring system integrity. These vulnerabilities are especially pronounced in mobile ad hoc networks (MANETs), where the dynamic topology and lack of centralized control make robust authentication and key agreement critical components of network security. Conventional two-factor authentication schemes, while widely used, often fall short against attacks such as smart card loss, offline password guessing, identity spoofing, and replay attacks. These weaknesses expose networks to significant risks, necessitating advanced detection mechanisms. To address these challenges, this paper proposes a novel hybrid metaheuristic approach integrated with elliptic curve cryptography (ECC) for enhanced two-factor authentication in MANETs. The proposed method optimizes malicious node detection by combining metaheuristic optimization techniques with ECC’s lightweight, secure key exchange. This approach significantly improves detection accuracy, increases the number of active nodes, and optimizes residual energy, thereby enhancing both security and operational efficiency. Simulation results demonstrate that the proposed system outperforms existing methods in identifying malicious nodes while maintaining energy efficiency, making it particularly suited for resource-constrained MANETs. By addressing the limitations of traditional authentication schemes, this hybrid approach offers a robust solution for securing dynamic and vulnerable network environments, paving the way for more resilient intrusion detection systems in dynamic networks.