Abstract: This article is dedicated to the problem of detecting intrusions of unknown type based on neural networks that bypass the system of information security in automated data processing systems and are not recognized as spiteful. Development of the means, methods and measures for detecting or preventing such hidden attacks is of particular relevance. Methodological research on the development of procedure for detecting intrusions are based on the achievements of systemic analysis, systemic-conceptual approach towards protection of information in automated data processing systems and achievements of the theory of neural systems in the area of ensuring information security. The object of this research is the intrusions of unknown type in automated data processing systems. The subject is the neural networks, namely neural networks of direct action. The main result lies in the development of neural network of direct action in form of the diagram of neural network links for detecting intrusions. For solving this task, the author developed:
1) The system of input indicators of the neural system;               
2) Scales for the assessment of values of the formed indicators;
3)  General procedure for detecting intrusions based on neural networks, the essence of which consists in implementation of the following sequence of actions: a) formation of the list of all the main parties to the process of detection of intrusion; b) formation of the set of parameters that characterize each of them; c) formation of the set of numerical characteristics for each parameter using the assessment scales of the formed indicators; d) analysis of the parameters of the configuration of neural network
The developed procedure may serve as the basic in further practical developments of the concept of detecting intrusions of unknown types based on neural networks.

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 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.