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@article{172275,
        author = {Likith G and Kushaal G P and Gaurav Dhull and Raesa Razeen},
        title = {IntruAlert - A High Performance Network Intrusion Detection System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {2645-2652},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172275},
        abstract = {In today’s rapidly evolving digital landscape, protecting network infrastructure from unauthorised access and cyber threats is of paramount importance. IntruAlert is an advanced Network Intrusion Detection System (NIDS) engineered to proactively monitor, detect, and mitigate network threats in real-time. By integrating cutting-edge technologies like machine learning, signature-based detection, and anomaly detection algorithms, IntruAlert delivers comprehensive protection against both known and emerging cyberattacks.
The system persistently analyses network traffic to detect irregular patterns that may signify intrusions. It features an extensive threat signature database and employs heuristic methods to identify zero-day vulnerabilities. IntruAlert’s modular design ensures seamless integration into existing network infrastructures, offering scalability and adaptability to cater to various organisational needs.},
        keywords = {},
        month = {January},
        }