A Browser-based Cross Site Request Forgery Detection Model. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Zhang, Jingyu; Hu, Hongchao; Huo, Shumin
• Is Part Of: Journal of physics. Volume 1738:Issue 1(2021)
• Publication Date: 2021-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1738/1/012073
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: CSRF is one of the most serious cyber attacks, and has been recognized as the main threat and one of the ten most serious vulnerabilities in web applications. The CSRF attack is when the attacker uses the implicit authentication mechanism of the HTTP protocol and the cookies cached in the browser to pass the authentication, and then executes the attack on the target website. In this article, we propose a browser-based CSRF detection model, which can detect CSRF attacks by analysing HTTP requests and web page content, thereby identifying the attacker's CSRF attacks.