Develop a Novel Weighed Quantum Ant Lion Optimization Algorithm to Enhance Security Mechanisms in Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) are being employed in security-sensitive applications; hence, they have become subjects of several security attacks comprising Denial-of-Service (DoS) attacks, data eavesdropping and compromised nodes. To overcome these challenges, researchers have introduced a new type of approach, which is Weighed Quantum Ant Lion Optimization (WQALO), to heighten security in clustered WSN. Its aim is to successfully detect and address these security vulnerability issues within numerous clusters by taking advantage of the adaptability and robustness of natural optimization techniques. This approach has integrated quantum features into the Ant Lion Optimization approach, and through this, it improves its global search capacity and guarantees convergence to optimal solutions in less time. In every cluster, the important security issues concerned with the data confidentiality, node authorization and energy consumption are weighted by taking a weighted approach. Through WQALO implementation, clusters will be able to cooperate to measure security threats and reduce them, increasing the usage of resources and network resilience. Studies of the WQALO method proposed indicate an improvement of 25% in DoS attack defense, 30% in the interception of data, a 20% reduction in vulnerability attacks on nodes and an 18% enhancement in power consumption compared to the currently used security mechanisms. The above results illustrate that WQALO performs well in developing strong and secure clustered WSN systems that can resist advanced cyberattacks and also guarantee the integrity and reliability of information sent in critical applications.