Abstract: This article is dedicated to construction of the system of information security in automated data processing systems that function by analogy with the human immune system. The subject of this research is the development of the procedure for countering external intrusions of viruses, spam, and other destructive software programs in automated data processing systems. The object of this research is the systems of ensuring information security in automated data processing systems and human immune system. Methodological research on elaboration of the procedure for identification of intrusion is conducted via methods of artificial intelligence, systemic analysis, theory of neural and immune systems in the sphere of ensuring information security based on the achievements of systemic analysis and a systemic-conceptual approach towards information security in automated data processing systems. The main result lies in the developed general procedure for the functionality of the system of ensuring information security in countering external intrusions in the form of block-diagram and its description. The procedure is based on the idea of similarity in functionality of the mechanisms and procedures for protection against external intrusions in both, human immune system and automated data processing system, as well as drawing parallel between them. The main peculiarity of the developed procedure lies in its applicability to the accepted classification of the initial external environment of intrusion onto physical, information, field, and infrastructure environments. Such approach guarantees the novelty of the development from the perspective of constant updating of human immune system countering mechanisms to the external intrusions and its application for each environment in applicable to automated data processing systems.

Abstract: The subject of this research is the system of creating mechanisms of information from internal threats in automated data processing systems similar to the mechanism of human immunity. The object of this research is the mechanism of human immunity and systems of ensuring information security in automated data processing systems. The goal of this work lies in the development of the universal scheme of functionality of the mechanism of human immunity against internal threats in form of the procedure, and develop on its basis the immune-like scheme for countering internal threats applicable to the systems of ensuring information security. Methodological research on the development of procedure for detecting internal threats in the mechanism of human immunity is carried out via the methods of systemic analysis in area of ensuring information security. Special attention is given to such aspects as consistency and adaptability of the mechanisms of human immunity applicable to the systems of ensuring information security. This article introduces the new solution to the task of adapting the universal scheme of functionality of the immune system in countering internal threats in the systems of ensuring information security based on the principle of demarcation of the elements to “known/alien” and implementation of the procedure to “destroy” threat, the so-called “Trogotcytosis” (“gnaw”). The developed procedures may serve as the basic schemes in further practical studies of the immune-like systems of ensuring informations security.

Abstract: The subject of this research is the analysis of possible implementation of the mechanisms of functionality of human immune system applicable to information security systems in automated data processing systems. The objects of this research are the human immune system, information security systems, and automated data processing systems. The research is conducted on the basis of achievements of systemic-conceptual approach towards information protection in automated data processing systems, developed within the framework of the project sponsored by the Russian Foundation for Basic Research No. 19-01-00383 on creation of intelligent information protection systems based on the neural network intrusion detection systems and  the mechanisms of artificial immune systems. The article reviews similarity and difference between human immune system and information security systems. Special attention is given to identification of peculiarities of functionality of the mechanisms on detection of harmful intrusions into these systems respectively. Methodological research on the topic are carried out using the achievements in the area of creation of neural network intrusion detection system, built on the basis of artificial immune mechanisms that function similar to human immune system. The main result consists in the conclusion that adaptive information security systems containing the means and mechanisms of protection and built by analogy with the human immune system, may provide successful and effective protection of information in automated data processing systems. The specificity and importance of this conclusion is substantiated by the fact that it can be implemented despite the absence of full analogy between human immune system and information security system; moreover, multiple mechanism of protection implemented in human immune system are absent in the information security system, or the other way around.

Abstract: The subject of the research is the problem of identifying and countering intrusions (attacks) in information security systems (ISS) based on the system-conceptual approach, developed within the framework of the RFBR funded project No. 19-01-00383. The object of the research is neural networks and information security systems (ISS) of automated data processing systems (ADPS). The authors proceed from the basic conceptual requirements for intrusion detection systems - adaptability, learnability and manageability. The developed intrusion detection procedure considers both internal and external threats. It consists of two subsystems: a subsystem for detecting possible intrusions, which includes subsystems for predicting, controlling and managing access, analyzing and detecting the recurrence of intrusions, as well as a subsystem for countering intrusions, which includes subsystems for blocking / destroying protected resources, assessing losses associated with intrusions, and eliminating the consequences of the invasion. Methodological studies on the development of intrusion detection procedures are carried out using artificial intelligence methods, system analysis, and the theory of neural systems in the field of information security. Research in this work is carried out on the basis of the achievements of the system-conceptual approach to information security in ADPS.The main result obtained in this work is a block diagram (algorithm) of an adaptive intrusion detection procedure, which contains protection means and mechanisms, built by analogy with neural systems used in security systems.The developed general structure of the intrusion detection and counteraction system allows systematically interconnecting the subsystems for detecting possible intrusions and counteracting intrusions at the conceptual level.

Abstract: The subject of the research is the concept of creating intelligent information protection systems based on neural network intrusion detection systems in automated data processing systems, developed as part of the funded project of the RFBR No. 19-01-00383. The object of the study is the intelligent information protection systems in automated data processing systems, built on the basis of neural intrusion detection systems, and later on the mechanisms of artificial immune systems. The authors consider adaptability, learning ability and controllability as the main conceptual requirements for the intrusion detection systems. Particular attention is focused on the construction of a flexible intelligent information protection system containing intrusion detection systems in both the nodes of the structural components of automated data processing systems, and in data transmission networks between structural components. Methodological studies of the chosen research direction are carried out using the methods of artificial intelligence, system analysis, the theory of intelligent information systems in the field of artificial intelligence. The work uses the achievements of a system-conceptual approach to information protection in automated data processing systems. The main result of the study is the conclusion that successful protection of information in automated data processing systems can only be carried out in a network in the form of interconnected local intrusion detection systems using neural network technologies combined into a single head center based on a system-conceptual approach. To combat unauthorized intrusions, it is necessary to adopt a unified systematic approach based on uniform legal, organizational and technical measures to protect information. The application of a system-conceptual approach to the creation of intrusion detection systems based on neural network technologies will contribute to the development of new tools, methods and activities for the intelligent management of information security in automated data processing systems.