• Sai Satav
• Mrunali Gavhane
• H. R. Kulkarni
• Sheela Satav

In today’s digital era, the rapid expansion of technology has significantly increased the risks associated with cyber threats and attacks. Traditional cybersecurity methods are often insufficient to detect and respond to the complex and evolving nature of modern threats. Artificial Intelligence (AI) has emerged as a transformative solution, enabling real-time threat detection, predictive analysis, and automated incident response. Through machine learning (ML), deep learning (DL), and advanced data analytics, AI-based systems can identify unusual patterns, detect zero-day vulnerabilities, and mitigate threats faster than human-driven approaches. These intelligent systems enhance detection accuracy, reduce false positives, and improve the overall efficiency of network defense mechanisms. However, challenges such as data privacy, model bias, and vulnerability to adversarial attacks remain significant areas of ongoing research. The integration of AI in cybersecurity thus represents an essential step toward building adaptive, intelligent, and resilient digital defense infrastructures.

AI-Driven Cybersecurity: Enhancing Threat Detection and Response Mechanisms

"AI-Driven Cybersecurity: Enhancing Threat Detection and Response Mechanisms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 1, page no.602-605, January-2026, Available :http://www.jetir.org/papers/JETIRHG06079.pdf

"AI-Driven Cybersecurity: Enhancing Threat Detection and Response Mechanisms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 1, page no. pp602-605, January-2026, Available at : http://www.jetir.org/papers/JETIRHG06079.pdf