International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-8 Issue-6, August 2019 4526 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number F8842088619/2019©BEIESP DOI: 10.35940/ijeat.F8842.088619 Abstract: The rapid development of information technology has strengthened the importance of the information risk management system. Integrated systems for storing and processing information, its transmission channels, as well as the information itself, are strategically essential objects of national security. The growing volumes of statistical data, as well as the traditional uncertainty and incompleteness of information on the nature of potential threats, determine the need to use new approaches for risk analysis. The neuro-fuzzy model considered in the article is based on the advantages of fuzzy logic and artificial neural networks. The proposed neuro-fuzzy network is adapted for continuous risk analysis and iterative implementation of the analysis stage. It eliminates the disadvantages of the fuzzy logical model and takes full advantage of neural networks. This system copes well with large volumes of information since there is a direct correlation between the amount of data and the speed of network learning. The data provided by the network at the output is expressed in understandable terms and sufficient to make a balanced and reasoned decision on information risk management. Keywords : Neuro-Fuzzy Model, Risk, Information Risks, Risk Management, National Security. I. INTRODUCTION In modern political realities, one of the essential factors in ensuring the security of both the state as a whole and individual business entities is information security. Now in the era of the global spread of information technology, state security is more than ever exposed to the influence of information threats. That is why the effectiveness of the information risk management system is becoming a critical national security issue [1-3].It should be immediately determined that information security will be understood as the security of information resources and information systems from accidental or deliberate influences of a natural or artificial nature, fraught with damage to both the system as a whole and its individual elements. Revised Manuscript Received on August 20, 2019 * Correspondence Author Alla Khomutenko*, Finance Department of Odessa National Economic University, Odessa, Ukraine Alla Mishchenko, Department of International Relations, Faculty of Journalism and International Relations, Kyiv National University of Culture and Arts, Kyiv, Ukraine Artem Ripenko, Odessa Forensic Research Institute of Ministry of Justice of Ukraine, Odessa, Ukraine Olha Frum, Department of Industrial Economics, Odessa National Academy of Food Technologies, Odessa, Ukraine Zoreslava Liulchak, Department of Marketing and Logistics Lviv Polytechnic National University, Lviv, Ukraine Roman Hrozovskyi, Research Laboratory of the Department of Application of Information Technologies and Information Fight of the National Defence University of Ukraine named after Ivan Cherniakhovskyi, Kyiv, Ukraine Within the framework of this article, it is supposed to reduce such a broad concept as information risk to two categories:- associated with the leakage, alteration or destruction of information;- associated with a malfunction in the operation of software or hardware (caused by various factors of a natural or artificial nature) [4-5]. The information risk management scheme can be simplified represented in Fig. 1. Fig. 1.Information Risk Management. The primary stage of the risk management system is the identification and identification of risks: analysis of possible and existing vulnerabilities in the information processing and storage system, identification of potential external and internal threats, classification and verification of information of particular value to the state. The stage of risk analysis and assessment involves a qualitative and quantitative risk assessment, the result of which is information that allows you to make decisions about the necessary risk management measures. The set of steps to counter risks at the state level includes some measures aimed at reducing, adopting or counteracting, the decision on the use of which is taken at a senior level. The control and adjustment stage allows us to evaluate the effectiveness of the measures taken and, if necessary, launch the next iteration of the risk management cycle [6-7].Naturally, specialists have been dealing with these issues for more than a decade, and the mechanisms developed are quite useful. At the same time, the very nature of information risks, and the areas in which they arise suggests the need for constant re-evaluation and modernization of existing methods. As the key elements of the system, it is possible to single out the stages of analysis and risk assessment; it is for these points that it is proposed to test the tools of the neuro-fuzzy model. Information Risk Management System Methodology for identifying and identifying risks Risk Assessment and Analysis System Package of measures to cope with the risks Mechanisms for monitoring and adjusting results Tools of the Neuro-Fuzzy Model of Information Risk Management in National Security Alla Khomutenko, Alla Mishchenko, Artem Ripenko, Olha Frum, Zoreslava Liulchak Roman Hrozovskyi