International Journal of Scientific Research and Engineering Development

The rapid integration of Artificial Intelligence (AI) into digital systems has significantly changed modern cybersecurity. It has made automated threat detection, predictive analysis, and intelligent response possible. However, the combination of AI and cybersecurity brings some serious challenges. These include model vulnerabilities, data privacy issues, adversarial attacks, and the difficulty in explaining how systems operate. This research paper looks into the evolving relationship between AI and cybersecurity. It aims to close the gap between intelligent automation and secure system design. The study offers a detailed analysis of AI-driven cybersecurity solutions. These include machine learning-based intrusion detection systems, malware classification, phishing detection, and behavioral anomaly analysis. It also looks at new threats targeting AI models, such as adversarial machine learning, data poisoning, model evasion, and inference attacks. The paper pays particular attention to federated learning and explainable AI as promising ways to improve privacy and trust in security-critical settings. Additionally, this paper discusses the challenges of using AI-based security systems in real-life situations. These challenges include scalability, bias, lack of transparency, and integration with current security systems. Through a thorough review of recent literature, the paper highlights key research gaps and suggests a framework that connects strong AI methods with cybersecurity principles. By focusing on resilience, interpretability, and ethical issues, this work aims to guide future research in creating secure, trustworthy, and flexible AI-driven cybersecurity systems that can tackle both current and future digital threats.

Prof. Himanshu A. Tarale, Prof. Sharayu N. Konde,"Harmonizing Artificial Intelligence and Cybersecurity for Resilient and Autonomous Security Systems" International Journal of Scientific Research and Engineering Development, V9(1): Page(612-616) Jan-Feb 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.