DEVELOPMENT OF A METHOD FOR INVESTIGATING CYBERCRIMES BY THE TYPE OF RANSOMWARE USING ARTIFICIAL INTELLIGENCE MODELS IN THE INFORMATION SECURITY MANAGEMENT SYSTEM OF CRITICAL INFRASTRUCTURE

Abstract

In this article the authors focused on analyzing the possibilities of using artificial intelligence models for effective detection and analysis of cybercrimes. A comprehensive method using artificial intelligence algorithms such as Random Forest and Isolation Forest algorithms is developed and described to detect ransomware which is one of the main threats to information security management systems (ISMS) in the field of critical infrastructure. The result of the study is the determination of the compatibility of such methods with the requirements of ISO 27001:2022 emphasizing the importance of integrating innovative AI technologies into already existing security systems. In addition the article analyzes the potential advantages of such integration including compliance with the requirements of international information security frameworks. Keywords: Isolation Forest Random Forest critical infrastructure information security management system ISO 27001 cyber security cyber security standard cybercrime ISMS ransomware siem edr security monitoring antivirus machine learning computer networks information systems.