IMPACT OF ARTIFICIAL INTELLIGENCE ON MODERN CYBER SECURITY THREAT DETECTION

Artificial Intelligence (AI) has emerged as a transformative technology in modern cyber security, especially in the detection and prevention of sophisticated cyber threats. Traditional security systems largely depend on rule-based and signature-based detection mechanisms, which are often ineffective against zero-day attacks, advanced persistent threats (APTs), and rapidly evolving malware. The increasing complexity and frequency of cyber-attacks have made it necessary to adopt intelligent and automated security solutions. The main objective of this study is to examine the impact of Artificial Intelligence on modern cyber security threat detection, identify its advantages over traditional security approaches, and analyze the challenges associated with its implementation. The study adopted a descriptive research methodology using survey design. Data were collected from students and staff of the Faculty of Computing, Bayero University Kano, through structured questionnaires and relevant secondary sources such as journals, textbooks, and online publications. The data collected were analyzed using simple percentage and descriptive statistical methods. The findings reveal that AI-based security systems significantly improve threat detection accuracy, enable real-time monitoring, reduce human error, and enhance automated response to cyber incidents. However, issues such as high implementation cost, data privacy concerns, and adversarial AI attacks remain major challenges. The study concludes that Artificial Intelligence plays a critical role in strengthening modern cyber security frameworks. It recommends increased investment in AI-driven security infrastructure, continuous training of cyber security professionals, and the development of ethical and regulatory frameworks to guide AI deployment in cyber security.