Lightweight Genetic Algorithms and RandomForest Based IoT Intrusion Detection

Due to the development of advance smart devices like IoT, Cyber attacks increases, which leads a requirement of efficient Cyber attack detection in IoT devices. In this context, we proposed a optimized cyber attack detection approach for IoT devices. Our proposed approach is the combination of random forest based feature selection techniques and genetic algorithm based hyper parameters selection method. We test the performance of our proposed approach through standard parameters like accuracy, recall, precision, and F1 score, and our proposed approach perform well in all the parameters.