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@article{190083,
        author = {Mrs. Yeshodha R and Ms. Noorain Firdose and Ms. Priyanka G},
        title = {Generative AI Revolution in Cybersecurity: A Comprehensive Review of Threat Intelligence & Operations},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {8},
        pages = {323-331},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190083},
        abstract = {In today’s hyper-connected digital environment, cyber threats are becoming increasingly sophisticated, posing significant challenges to organizations and individuals worldwide. Traditional cybersecurity systems often struggle to respond quickly and intelligently to dynamic attack patterns. Generative Artificial Intelligence (GAI) is emerging as a transformative force in cybersecurity by enabling automated threat detection, predictive analysis, and intelligent incident response. Leveraging advanced machine learning and deep learning models, GAI can analyze massive volumes of threat data, simulate potential attack scenarios, and generate adaptive defense strategies with minimal human intervention. This study provides a comprehensive review of GAI applications in threat intelligence and cybersecurity operations, examining its role in anomaly detection, intrusion prevention, and vulnerability assessment. Furthermore, the paper discusses the limitations and ethical risks associated with GAI, including model bias, data misuse, and adversarial exploitation. The research concludes by emphasizing the importance of secure AI deployment, continuous learning frameworks, and regulatory alignment to ensure trustworthy and resilient cybersecurity ecosystems powered by Generative AI.},
        keywords = {Generative Artificial Intelligence (GAI), Cybersecurity, Threat Intelligence, Machine Learning, Deep Learning, Anomaly Detection, Automation, AI Ethics, Security.},
        month = {December},
        }