AI-Driven Cybersecurity: Transforming Defense Strategies with Machine Learning

Authors

  • Narendra Kumar NIET NIMS University, Jaipur, India Author

DOI:

https://doi.org/10.64758/jrjwc781

Keywords:

Privacy Concerns, Ethical Frameworks, Predictive Analysis, Threat Detection

Abstract

This research examines the transformative effect of AI, particularly ML, on cybersecurity defense strategies. It delves into how AI transforms threat detection, predictive analysis, automated responses, and ethical frameworks, with integration challenges as a side focus. The qualitative methodology applied, including expert interviews and case studies, indicates that AI improves threat detection accuracy, predictive capabilities, and automated responses significantly, but the challenges of ethics and integration remain central. Such results highlight the urgency for more effective prediction models, adequate contextual responses, and stronger moral guidelines to appropriately utilize AI within cybersecurity.

Published

2025-07-01

How to Cite

AI-Driven Cybersecurity: Transforming Defense Strategies with Machine Learning. (2025). JANOLI International Journal of Computer Science and Engineering, 1(3). https://doi.org/10.64758/jrjwc781

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