The aim is to present that prevention in cyberspace is a complex technological, but also social process, which requires an integrated approach.
Abstract
The scientific paper analyses the role and capabilities of artificial intelligence (AI) in improving cybersecurity, with a special focus on the social, educational and technological challenges of preventive application. The first chapter is dedicated to the conceptual and theoretical definition of AI, cyberspace and cybersecurity, as well as the logical connection of the aforementioned phenomena and processes. The ability of AI to process large amounts of data, recognise behavioural patterns, identify threats and offer responses in real time suggests that it is an important instrument for improving cybersecurity. The second chapter is dedicated to the role of AI in preventing cyber threats with the aim of presenting the advantages of using new technologies in preventing, detecting, protecting, responding and maintaining the security of systems and their components. In this context, in addition to analysing the technological aspects of the use of AI, attention is paid to the social and educational challenges that are indispensable for the efficient functioning and protection of systems in cyberspace. Using descriptive and explanatory methods of analysis and synthesis methods, the aim is to present that prevention in cyberspace is a complex technological, but also social process, which requires an integrated approach.
A structured taxonomy is proposed to organize various dimensions of AI-driven cybersecurity; review them critically; and finally, discuss key challenges, open problems, and emerging trends.
As digital transformation accelerates and the complexity of cyberattacks continues to rise, cybersecurity has become a critical challenge for governments, businesses, and individuals. At the same time, the rapid development of Artificial Intelligence (AI) is profoundly transforming the field of cybersecurity. AI not on...
Jun Zhu· Exploring Science Academic C...· 0 citations
Cyberattacks are becoming more frequent and sophisticated in today’s digital world, rendering conventional security measures inadequate. In order to increase the accuracy of cyber threat detection, this study investigates the application of deeplearning methods to increase the accuracy of cyber threat detection. A cybe...
Devyansh Sharma, Inderdeep Kaur, Krishika Gupta et al.· International Conference on...· 0 citations
A comprehensive review of XAI techniques in industrial cybersecurity, focusing on industrial SOC environments and operational security workflows, and identifies open research directions and opportunities for developing trustworthy, operationally viable, and domain-specific XAI-enabled cybersecurity solutions for indust...
Amr S. Mohamed, Charlotte Fritz, A. M. Saber et al.· 0 citations
The findings indicate that AI can improve the speed, scalability, adaptability, and proactive capabilities of cybersecurity systems, however, challenges including data quality, false positives and negatives, adversarial attacks, privacy risks, lack of explainability, computational requirements, and ethical concerns rem...
Gurwinder Singh· International Journal of Sci...· 0 citations
The literature review indicates that AI can improve cybersecurity threat detection and legal information processing but also introduces risks involving inaccurate outputs, malicious use, manipulated information, transparency, and accountability, which support continued development of AI systems that are secure, transpa...