Identification of Abnormal Functioning of Devices of Cyber-Physical Systems

This paper undertakes the task of determining the information security state of autonomous objects using information obtained through a side acoustic channel. The basic prerequisites for using externally independent monitoring systems to monitor the state of objects at risk of the influence of threats to information security are considered. An experiment to study the functioning parameters of unmanned vehicles in various functioning situations was performed. The appearance and statistical characteristics of the signals, which enable the identification of abnormal deviations during the operation of unmanned vehicles, are shown. Furthermore, an algorithm of two- and three-class classification of the states of the studied objects is presented. It was found that analysis based on the obtained sample is acutely sensitive to any changes in the software and hardware configuration. Simultaneously, with a minimum time of accumulation of statistical information using the proposed approach based on a given threshold, it becomes possible to determine the point at which the attack was begun. The proposed approach model implies the possibility of using various mathematical apparatus, statistical methods, and machine learning to achieve specified indicators for assessing the state of an object’s information security.