Swarm intelligence for IoT attack detection in fog-enabled cyber-physical system.

•Network integration in cyber-physical systems (CPSs) leads to cyber attacks due to the integration of insecure networking devices.•A new swarm-based feature selection algorithm is proposed to improve attack detection in an IoT-based CPS environment.•The proposed algorithm uses enhanced chicken swarm optimization (ECSO) with self-learning ability-based feature selection to select relevant features from preprocessed data.•The proposed ECSO-based ensemble classifier is tested on the NSL-KDD dataset and shows effective performance using various statistical measures.