Automatic Identification of Web Vulnerabilities and Risks in Web Applications

Authors

  • Dr. Khyati Rami, Prof. Prashant Halvadiya,Prof. Roshni Patel

Keywords:

Web vulnerability; automated risk assessment; machine learning; DAST; CVSS; dynamic scanning.

Abstract

Web applications have proliferated across domains, yet their mushroomingintricacy has exacerbated susceptibility to security dangers. Standard techniques likeStatic Application Security Testing and signature-centered scanners are confined inaddressing groundbreaking and sophisticated assaults, frequently generating high false

References

R. H. Zakon, “Hacker techniques and exploits: Emerging web application security threats,” IEEE Internet Computing, vol. 25, no. 3, pp. 56–64, May–Jun. 2021.

OWASP Foundation, OWASP Top Ten Web Application Security Risks 2021. [Online]. Available: https://owasp.org/www-project-top-ten/

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Published

2024-04-25

How to Cite

Dr. Khyati Rami, Prof. Prashant Halvadiya,Prof. Roshni Patel. (2024). Automatic Identification of Web Vulnerabilities and Risks in Web Applications . Journal of Computational Analysis and Applications (JoCAAA), 33(4), 907–920. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3311

Issue

Vol. 33 No. 4 (2024): Selected Papers on Computational Techniques Across Multidisciplinary Fields: Innovations and Applications

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.