Wagging-Based Whale Optimization Algorithm to Enhance the Prediction of Intrusions in IoT Network

The rapid growth of the Internet of Things (IoT) has led to an increased need for robust intrusion detection systems to safeguard IoT networks against malicious activities. Traditional methods have shown limitations in accurately detecting and predicting intrusions due to the dynamic and heterogeneous nature of IoT environments. A novel approach called the Wagging-based Whale Optimization Algorithm (WWOA) is proposed for enhancing the prediction of intrusions in IoT networks. The WWOA integrates the collective intelligence of whale optimization with the dynamic adaptability of the wagging mechanism to optimize the performance of intrusion detection systems. The algorithm's effectiveness is demonstrated through comprehensive experiments, showcasing its capability to improve the accuracy and efficiency of intrusion prediction in IoT networks. By leveraging the WWOA, IoT networks can achieve heightened security levels and maintain the integrity of their operations in the face of evolving cyber threats.