Related to the development and research of methods for ensuring computer security of unmanned vehicles in the information infrastructure of a smart city approaches are considered. The approaches are based on nonparametric statistics methods for evaluating changes in the information states of controlled UMV resources, which include communication channel, processor, and memory. It is proposed to evaluate the changes for each of these resources in such characteristics as the degree of resource loading and its rate of change. State recognition is performed under conditions of a lack of a priori information about the properties of the intrusion source and the stochastic nature of the recognized events. The presented approach is based on dynamic estimation of information States of UMV resources using Markov sequences.

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The purpose of the production processes’ states simulation has two constituents. The first is to ensure the effective operation of technological facilities. The second is to improve the quality and competitiveness of the produced products. The proposed new scientific approach aims to develop the known statistical methods in the following direction. They are to be adopted for monitoring accuracy and stability of production processes: real-time processing of large amount of current data, large volumes of a priori information used for decision-making, adjusting the parameters of the monitoring system, critical technological conditions detection. It can prevent great economic damage or even catastrophic consequences.

The adaptive model and structure of the intrusion detection system (IDS) based on the analysis of traffic in the channel “UMV-dispatch center”, which is based on immunological principles, is proposed. Rules classify objects belonging to several classes at the same time with different degrees of belonging. Recognition of the state of network traffic is carried out in conditions of lack of a priori information about the properties of the intrusion source and the stochastic nature of the recognized events. To increase the level of reliability of intrusion detection in the system, adaptive dynamic adjustment of decision-making rules on classification and operational States of UMV traffic is performed.

The development of artificial intelligence and unmanned vehicles built on the basis of artificial intelligence use requires paying great attention to information security issues. For this purpose, we propose the use of the artificial immune system apparatus as a heuristic method for detecting incidents of intrusion into the unmanned vehicles security infrastructure, where the information security plays a special role in the channels of information exchange. In this paper, we study mathematical models of immune response enhancement of artificial immune system, which are systems of ordinary differential equations. For the first time, it was proposed to consider the degree of damage to the unmanned vehicles resource (s), and, as a result, their ability to effectively perform protective functions; to consider unmanned vehicles virus attacks as a multiplicative function; to accumulate an antivirus database ahead of time to improve the effectiveness of anti-virus measures.