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@article{192801,
        author = {V.MANJULA and T.NIKILESUVARAJAN and K.PRAKASH and S.RUDHRABALA},
        title = {A Comprehensive Analysis of Network Intrusion Detection Systems (NIDS) and Robust Defense Frameworks for Secure Enterprise Networks},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {2051-2053},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192801},
        abstract = {The rapid expansion of high-speed networks and cloud-integrated systems has made Network Intrusion Detection Systems (NIDS) a cornerstone of modern cybersecurity. While traditional firewalls filter traffic based on predefined rules, NIDS provides an essential layer of "defense-in-depth" by monitoring internal and external traffic for sophisticated patterns of unauthorized access, data exfiltration, and lateral movement. This study presents an analytical overview of evolving NIDS technologies, comparing traditional signature-based methods with modern anomaly-based approaches powered by machine learning. We examine how these systems identify threats such as Distributed Denial of Service (DDoS), zero-day exploits, and insider threats while highlighting the challenges of reducing false-positive rates in high-velocity data environments.},
        keywords = {Network Intrusion Detection Systems, Distributed Denial of Service, Threats, Cyber Security},
        month = {February},
        }