Abstract
The increasing sophistication of cyber threats has propelled artificial intelligence (AI) to the forefront of cybersecurity innovation. This paper explores the transformative potential of next-generation AI technologies, including deep learning, reinforcement learning, and hybrid models, in addressing the dynamic cybersecurity landscape. It examines practical applications in malware detection, intrusion detection systems, endpoint protection, and threat intelligence platforms, highlighting AI's ability to enhance predictive and real-time defenses. Furthermore, the discussion addresses ethical concerns, adversarial risks, and evolving challenges, emphasizing the necessity of collaborative eorts among researchers, policymakers, and industry stakeholders to ensure secure and ethical AI deployment. The implications for national security are profound, with AI proving indispensable in protecting critical infrastructure, safeguarding economic systems, and maintaining the integrity of democratic institutions. As AI redefines cybersecurity, the article calls for sustained innovation, ethical governance, and strategic investments to harness its full potential.
Keywords
Cybersecurity, Artificial Intelligence, Deep Learning, Reinforcement Learning, Hybrid Models, Malware Detection, Threat Intelligence, National Security, Ethical AI, Endpoint Protection.
Citations
IRE Journals:
Feyisayo Ogunmade
"Next-Generation AI Technologies in Cybersecurity: Emerging Trends and Applications" Iconic Research And Engineering Journals Volume 8 Issue 5 2024 Page 709-719
IEEE:
Feyisayo Ogunmade
"Next-Generation AI Technologies in Cybersecurity: Emerging Trends and Applications" Iconic Research And Engineering Journals, 8(5)
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