CROSS SITE REQUEST FORGERY DETECTION

Musku Revanth Reddy; Meka Nithin Reddy; A Swamy Goud

CROSS SITE REQUEST FORGERY DETECTION

April 2023

Vol-9, Issue-2

Paper ID: 19663

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Information Technology

Keywords

Machine Learning Random Forest Cross-site Black Box

Abstract

In this project, we propose a methodology to leverage Machine Learning (ML) for the detection of web application vulnerabilities. Web applications are particularly challenging to analyses, due to their diversity and the widespread adoption of custom programming practices. ML is thus very helpful for web application security: it can take advantage of manually labeled data to bring the human understanding of the web application semantics into automated analysis tools. We use our methodology in the design of Mitch, the first ML solution for the black-box detection of Cross Site Request Forgery (CSRF) vulnerabilities. Mitch allowed us to identify 35 new CSRFs on 20 major websites and 3 new CSRFs on production software.

License

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

Author Information

#	Name	Institute / Affiliation
1	Musku Revanth Reddy	B.V.Raju Institute of Technology
2	Meka Nithin Reddy	B.V.Raju Institute of Technology
3	A Swamy Goud	B.V.Raju Institute of Technology

How to Cite

Use the following formats to cite this article in your research.

APA Style

Reddy, Musku Revanth, Reddy, Meka Nithin, & Goud, A Swamy (2023). CROSS SITE REQUEST FORGERY DETECTION. International Journal of Advance Research and Innovative Ideas In Education, 9(2), 1555-1560.

MLA Style

Reddy, Musku Revanth, et al. "CROSS SITE REQUEST FORGERY DETECTION." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 2, 2023, pp. 1555-1560.

IEEE Style

Musku Revanth Reddy, Meka Nithin Reddy, and A Swamy Goud, "CROSS SITE REQUEST FORGERY DETECTION," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 2, pp. 1555-1560, 2023.

Vancouver Style

Reddy Musku Revanth, Reddy Meka Nithin, Goud A Swamy. CROSS SITE REQUEST FORGERY DETECTION. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(2):1555-1560.

Harvard Style

Reddy, Musku Revanth, Reddy, Meka Nithin, & Goud, A Swamy (2023) 'CROSS SITE REQUEST FORGERY DETECTION', International Journal of Advance Research and Innovative Ideas In Education, 9(2), pp. 1555-1560.

Chicago Style

Reddy, Musku Revanth, Meka Nithin Reddy, and A Swamy Goud. "CROSS SITE REQUEST FORGERY DETECTION." International Journal of Advance Research and Innovative Ideas In Education 9, no. 2 (2023): 1555-1560.

Turabian Style

Reddy, Musku Revanth, Meka Nithin Reddy, and A Swamy Goud. "CROSS SITE REQUEST FORGERY DETECTION." International Journal of Advance Research and Innovative Ideas In Education 9, no. 2 (2023): 1555-1560.