A Hybrid Heuristic Optimizer for IDS using Genetic with KNN

The Internet of Things (IoT) is a distributed network of physical entities ("things") for exchanging data over the Internet. These things may be equipped with sensors, actuators, software, and communication technologies. The IoT network can deliver substantial benefits to our society and economy, including better health services and safer societies. However, some security and safety challenges are rapidly increasing, and their solutions are not clearly defined. The work uses genetic algorithms to address intrusion detection systems (IDS) for IoT networks. It is a hybrid combination of a genetic algorithm and K-Nearest Neighbors (KNN) technique to solve the IDS in IoT networks with the aim of lightweight and accurate performance. The proposed algorithm has been analyzed and compared with the other existing models. Extensive simulation results demonstrate our suggested algorithm’s effectiveness and ability to attain 99% accuracy.