IADF-CPS: Intelligent Anomaly Detection Framework towards Cyber Physical Systems

Cyber–Physical Systems (CPSs) becoming one of the most complex, intelligent, and sophisticated system. Ensuring security is an important aspect towards CPSs. However, increase in complexity attacks CPSs, conventional anomaly detection methods are facing problems also growth volume data becomes challenging which requires domain specific knowledge that could be applied directly to analyze these challenges. In order overcome this problem, various deep learning based system developed. research, we propose approach by integration intelligent technique named Convolutional Neural Network (CNN) with Kalman Filter (KF) Gaussian-Mixture Model (GMM). The proposed model used for identifying detecting anomalous behavior This framework consists two process. First pre-process transforming filtering original into new format achieved privacy preservation data. Secondly, GMM-KF integrated CNN accurately estimated posterior probabilities legitimate events