AI-Enhanced Cyber Threat Detection and Response Systems
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Abstract
In this era of ubiquitous and highly developed cyber dangers, cybersecurity has emerged as an essential issue for modern organisations. Interest in using AI to improve cyber threat detection and response skills is on the rise as conventional approaches fall behind the dynamic threat environment. Recent advancements, problems, and future prospects are highlighted in this review paper's thorough overview of cyber threat detection and response systems augmented with AI. At the outset, we cover the basics of artificial intelligence (AI) in cybersecurity and trace the development of systems to identify cyber threats. We continue by outlining the benefits and drawbacks of supervised, unsupervised, and reinforcement learning, three of the AI-driven threat detection methods now available. Here, we show how AI-powered systems may effectively mitigate cyber risks in many sectors using real-world applications and case studies. Data quality, adversarial assaults, and ethical issues are just a few of the constraints and problems that we highlight and provide solutions for. Lastly, we go into the latest developments and potential paths forward in AI-powered cybersecurity, highlighting the need of working together across disciplines and continuously doing research to keep up with ever-changing threats. Researchers, practitioners, and policymakers may use this paper as a guide to better understand AI in cybersecurity, where it is now, and how to make future breakthroughs.
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