Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)

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Advancing Web Security: A Comprehensive Framework For Detecting And Mitigating Input Validation Vulnerabilities

Authors
B. Siva Lakshmi1, *, S. Keerthi Priya1, Ch. Dedeepya1, M. Vanitha1, S. Lakshmi Pratyusha1, G. V. G. K. Thanvi Priyusha1
1Information Technology, Vignan’s Institute of Engineering for Women (VIEW), Visakhapatnam, Andhra Pradesh, India
*Corresponding author. Email: dr.bolemsivalakshmi@gmail.com
Corresponding Author
B. Siva Lakshmi
Available Online 4 November 2025.
DOI
10.2991/978-94-6463-858-5_37How to use a DOI?
Keywords
SVM; Light GBM; Phishing; Genuine; Malicious
Abstract

In today’s online environment, websites face constant SQL injection and cross-site scripting attacks - mostly because many developers still do not properly check user inputs. Our team has built a smart scanning tool that finds these security holes, thoroughly checks websites for weak points, and gives practical advice on how to fix them before hackers can break in. Improvements include SVM, Light GBM, Machine Learning (ML) models to detect phishing. This tool not only identifies vulnerabilities but also provides blocking to protect against cyber threats, significantly enhancing web application security. Machine Learning (ML) models trained on historical attack data enabling the system to adjust and respond to emerging threat techniques while reducing incorrect alerts. A phishing attack is a simple way to obtain sensitive information from users. The main aim of attackers is to get information from users like their user ID, password, personal details, and bank details. The paper aims to detect phishing URLs using LightGBM and Support Vector Machine algorithm.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
Series
Advances in Computer Science Research
Publication Date
4 November 2025
ISBN
978-94-6463-858-5
ISSN
2352-538X
DOI
10.2991/978-94-6463-858-5_37How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - B. Siva Lakshmi
AU  - S. Keerthi Priya
AU  - Ch. Dedeepya
AU  - M. Vanitha
AU  - S. Lakshmi Pratyusha
AU  - G. V. G. K. Thanvi Priyusha
PY  - 2025
DA  - 2025/11/04
TI  - Advancing Web Security: A Comprehensive Framework For Detecting And Mitigating Input Validation Vulnerabilities
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 419
EP  - 430
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_37
DO  - 10.2991/978-94-6463-858-5_37
ID  - Lakshmi2025
ER  -