Adaptive Intelligence for Cyber Defense Evaluating Machine Learning Models for Real-Time Threat Detection

DOI

https://www.doi.org/10.59256/indjcst.20260501044

Published In

Volume 5, Issue 1 (2026)

Published Online

January-April 2026

Pages

317-325

Article Type

Original Article

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With the ascendency of digital infrastructure, the need for a good security is also on its increase. With the emergence of highly malicious cyber-attacks including ransomware, phishing, DDoS attacks as well as zero-day exploits, traditional security is becoming insufficient. With the advent of Artificial Intelligence (AI), we have witnessed an explosion in capabilities in real time response, predictive analytics, and the overall detection of threats. In this paper, we focus on the improvement of the AI evolution in place of the traditional cybersecurity models and also discuss the use of AI in automated defense mechanisms. It also analyzes the issues involved with cybersecurity driven by AI such as bias in the AI model, adversarial attacks and regulatory reasons. This research presents understanding of how and to what extend AI is adopted and utilized in cyber defense by employing a theoretical framework based on systems theory and the Technology Acceptance Model (TAM). The findings suggest that AI does play the role of mitigating cyber risks, and that some of the potential limitations AYI should help improve the development of more resilient cybersecurity strategies.