Rohit Kumar,
- Assistant Professor, Department of Computer Applications, Echelon Institute of Technology, Faridabad, Haryana, India
Abstract
Launch-Attack is a lightweight and practical threat-detection framework designed specifically for smaller web-automation environments, including setups that rely on tools such as Selenium. Rather than aiming to replace large enterprise-grade security platforms, the framework focuses on offering an accessible option for developers, testers, and researchers who need real-time monitoring without the heavy resource demands of traditional systems. The model relies on machine-learning techniques implemented through Scikit-learn, enabling it to detect common web-based threats such as cross-site scripting (XSS) attempts and malicious script-injection behavior. During evaluation using publicly available datasets, including portions of CIC-IDS2017, the framework achieved encouraging results: an overall detection accuracy of approximately 92%, a false-positive rate near 3%, and an average response time well under 1 sec. These performance characteristics highlight its suitability for continuous testing workflows and automated browser interactions. Additionally, its modest memory footprint, around 200 MB, makes it a practical choice for constrained environments. Future development aims to expand Launch-Attack’s compatibility to broader browser-based ecosystems and mobile automation platforms, further increasing its versatility and usability.
Keywords: Machine learning, cybersecurity, browser automation, threat detection, lightweight framework, freelance automation, web security, Selenium, Puppeteer
[This article belongs to Journal of Web Engineering & Technology ]
Rohit Kumar. Cybersecurity in Web Automation: A Machine Learning Approach to Lightweight Intrusion Detection. Journal of Web Engineering & Technology. 2026; 13(01):34-40.
Rohit Kumar. Cybersecurity in Web Automation: A Machine Learning Approach to Lightweight Intrusion Detection. Journal of Web Engineering & Technology. 2026; 13(01):34-40. Available from: https://journals.stmjournals.com/jowet/article=2026/view=235616
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Journal of Web Engineering & Technology
| Volume | 13 |
| Issue | 01 |
| Received | 20/06/2025 |
| Accepted | 28/09/2025 |
| Published | 05/01/2026 |
| Publication Time | 199 Days |
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