Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{144506,
        author = {Anind Dixit and Anind Dixit},
        title = {Web Based Intrusion Detection System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {12},
        pages = {32-35},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144506},
        abstract = {Web applications are growing rapidly and as the amount of web sites globally increases so do security threats. Complex applications often interact with third party services and databases to fetch information and often interactions require user input. Intruders are targeting web applications specifically and they are a huge security threat to organizations and a way to combat this is to have intrusion detection systems. Most common web attack methods are well researched and documented however due to time constraints developers often write applications fast and may not implement the best security practices. This report describes one way to implement a intrusion detection system that specifically detects web based attacks.},
        keywords = {Intrusion detection, Text Mining, Machine learning, Classification},
        month = {},
        }