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@article{180761,
        author = {Amit Kumar bachcha jha},
        title = {AI-Based Cybersecurity Threat Detection System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {2176-2177},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180761},
        abstract = {In the evolving landscape of digital transformation, cyber threats have become increasingly sophisticated. Traditional security systems often struggle to identify complex and dynamic attack patterns. This paper explores an AI-based cybersecurity threat detection system that leverages machine learning algorithms to detect anomalies and potential threats in real-time. By utilizing data-driven techniques such as supervised and unsupervised learning, AI enhances detection accuracy and response speed. This research outlines the architecture, implementation strategies, benefits, and limitations of AI-based security systems in modern enterprises.},
        keywords = {Artificial Intelligence, Cybersecurity, Machine Learning, Threat Detection, Intrusion Detection Systems},
        month = {June},
        }