OVERVIEW OF MODERN METHODS AND MEANS OF DETECTING OF SOCIOTECHNICAL ATTACKS

Abstract

Relevance. The rapid development of information technology and intensive data exchange are significantly changing the modern cybersecurity environment, creating new threats in the form of cyberattacks and fraud. Socio-technical attacks that use psychological manipulation to obtain confidential information or access to secure systems are particularly dangerous. Objective. Given this, the purpose of this paper is to provide a comprehensive review of existing solutions, technologies, and methods that can help organizations and private users combat sociotechnical threats. Methodology. The article studies modern methods of detecting sociotechnical attacks that use manipulative techniques. Various approaches to detecting such attacks are considered, including signature, behavioral, machine learning, metadata analysis, as well as social and psychological approaches. Particular attention is paid to interactive and simulation methods that allow organizations to test their preparedness for attacks by simulating real-world conditions. Scientific novelty. Hardware and software tools are described according to nine criteria (high level of protection, centralized management, ease of use, integration with other platforms, artificial intelligence, adaptability, offline capabilities, high cost, complexity of configuration) to detect and block sociotechnical attacks, which provide multi-level protection against sociotechnical threats. Conclusions. The findings show that educational and organizational measures remain key to raising user awareness and reducing the risk of successful attacks, and modern approaches to protecting against sociotechnical threats should be comprehensive and include both technical solutions and staff training. It is also important to continuously improve existing security measures and introduce the latest technologies to increase the effectiveness of protecting information systems from sociotechnical attacks.