ARTIFICIAL INTELLIGENCE IN CYBERSECURITY

Abstract

After the introduction, it has gained an interminable reputation, reproduction, and operation in the aspect of studies on cybersecurity. Because organizations are able to detect, respond as well as to forestall cyber-attack with great swivel and automation, artificial intelligence in cybersecurity has managed to achieve outstanding growth. As the hostile actions of cyber dispute continue to evolve and grow in severity, it frequently becomes fairly difficult for this goal to be reached as traditional security measures cannot provide an immediate response to advanced threats. AI-based security platforms leverage machine learning, neural networks, natural language capacities and behavioral architecture perspectives to observe network activities, recognize discrepancies, uncover malware, and even take actions without human intervention. These environments are superb at applying threat intelligence by exploring huge amounts of organised and unstructured data, mitigating the presence of false negatives and improving the security hygiene of the environment. At the same time, however, deployment of AI in cybersecurity is just as challenging due to adversarial machine learning, privacy related issues, data biases in models and the scarcity of quality data for deep learning. It has a scope of discussion and analysis in the present paper, for instance, and the main idea of computer-aided security management, exploring the most essential AI techniques, limitations observed, and what to expect in this area in the near future.