SMARTGUARD WSN: OPTIMIZED CLONE ATTACK DETECTION WITH MINIMAL RESOURCE OVERHEAD

Abstract

Wireless Sensor Networks (WSNs) are increasingly deployed in mission-critical applications, making them prime targets for clone attacks, where compromised nodes are duplicated to disrupt network integrity and security. Traditional clone detection mechanisms, though effective, often impose significant energy and memory overhead, thereby reducing the lifetime and efficiency of resource-constrained sensor nodes. To address these challenges, this paper proposes SmartGuard WSN, an optimized clone attack detection framework designed to achieve high security with minimal resource consumption. The framework integrates lightweight cryptographic primitives, probabilistic key distribution, and localized verification techniques to minimize communication and computation costs. By leveraging energyaware routing strategies and memory-efficient data structures, SmartGuard WSN significantly reduces overhead while maintaining robust detection accuracy. Experimental evaluations on simulated WSN environments demonstrate that the proposed model outperforms existing approaches in terms of energy efficiency, memory utilization, and detection rate. SmartGuard WSN thus offers a scalable and sustainable solution for securing WSNs against clone attacks, ensuring both network longevity and data integrity.