A Method Based on Employing Whale Optimization Algorithm to Defend Against Jamming Attacks in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are highly vulnerable to interference attacks due to their operation over open, shared media. Such attacks generate severe congestion, leading to denial of service and preventing legitimate nodes from connecting. This paper presents a defense strategy using the Whale Optimization Algorithm (WOA) to counter jamming in WSNs. The method restores network functionality through path switching, reducing energy consumption, improving Signal-to-Noise Ratio (SNR), lowering packet loss ratio (PLR), and increasing packet delivery ratio (PDR). WOA detects abnormal radio signal behavior from nodes, enhancing network robustness, sustaining high PDR, minimizing energy use, and preserving connectivity under severe, multi-type jamming. The approach was simulated and compared with Ant Colony Optimization (ACO) and Artificial Bee Colony (ABC) algorithms. WOA achieved a PDR of up to 0.9 with a single jammer, while ACO and ABC remained below 0.6. It delivered up to 90% of packets compared to less than 60% for the others. PLR averaged 0.44 for WOA, while ACO and ABC suffered near-total losses after two jammers. Energy efficiency improved significantly, with WOA consuming 39.5% less energy on average, and up to 90% less in some scenarios. SNR peaks reached 120 dB under constant jamming, consistently surpassing ACO and ABC. Additionally, WOA converged to optimal fitness in just two iterations, with an execution time of 0.075 seconds. Overall, WOA demonstrated superior performance in resilience, efficiency, and speed, making it a highly effective solution for defending WSNs against diverse jamming threats.