Using Machine Learning Techniques to Increase the Effectiveness of Cybersecurity

In today's world, a great number of organizations generate and accumulate large amounts of information, which is of great value to owners, and is also considered by attackers as a valuable resource for enrichment. Any data storage system has vulnerabilities that will be exploited during cyberattacks. The inability to build a system secure enough against unauthorized access to data, forces companies to respond on an ongoing basis to evolving technologies of misappropriation of information by developing more effective methods of identifying and combating cyberattacks. This article examines the features of the use of machine learning methods to identify illegal access by third parties to the information of individuals and legal entities with economic and reputational damage. The study considers methods of processing various types of data (numerical values, textual information, video and audio content, images) that can be used to build an effective cybersecurity system. Obtaining a high level of identification of unauthorized access to data and combating their theft is possible through the implementation of modern machine learning approaches, which are constantly improving by creating innovative data processing algorithms and the use of powerful cloud computing services, acting as an element to counter rapidly evolving technologies