The intersection of Artificial Intelligence and cybersecurity: Challenges and opportunities

The intersection of Artificial Intelligence and cybersecurity: Challenges and opportunities

Received on 13 January 2024; revised on 24 February 2024; accepted on 26 February 2024 | Adewale Daniel Sontan 1.* and Segun Victor Samuel 2
The article "The Intersection of Artificial Intelligence and Cybersecurity: Challenges and Opportunities" by Adewale Daniel Sontan and Segun Victor Samuel explores the transformative role of artificial intelligence (AI) in cybersecurity. The authors discuss foundational principles, advanced methodologies, and ethical considerations, highlighting how AI techniques such as machine learning and natural language processing are enhancing threat detection, vulnerability analysis, and incident response. They compare traditional methods with AI-driven approaches, emphasizing the benefits of automated scanning, threat prioritization, and adaptive risk assessment. The article also addresses ethical and privacy concerns, advocating for responsible decision-making, privacy protection, and transparency. Looking ahead, the authors discuss emerging trends like adversarial machine learning and zero trust security, which offer promising avenues for further exploration and enhancing digital resilience against evolving threats. The study concludes by emphasizing the need for robust ethical frameworks and privacy safeguards to ensure a safer digital future.The article "The Intersection of Artificial Intelligence and Cybersecurity: Challenges and Opportunities" by Adewale Daniel Sontan and Segun Victor Samuel explores the transformative role of artificial intelligence (AI) in cybersecurity. The authors discuss foundational principles, advanced methodologies, and ethical considerations, highlighting how AI techniques such as machine learning and natural language processing are enhancing threat detection, vulnerability analysis, and incident response. They compare traditional methods with AI-driven approaches, emphasizing the benefits of automated scanning, threat prioritization, and adaptive risk assessment. The article also addresses ethical and privacy concerns, advocating for responsible decision-making, privacy protection, and transparency. Looking ahead, the authors discuss emerging trends like adversarial machine learning and zero trust security, which offer promising avenues for further exploration and enhancing digital resilience against evolving threats. The study concludes by emphasizing the need for robust ethical frameworks and privacy safeguards to ensure a safer digital future.
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