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Research Article

Advanced Detection and Mitigation of Cross-Site Scripting Attacks through Intelligent JavaScript Code Injection Analysis

Open Access Peer Reviewed

Authors

  • Ashmit Gupta1
  • Neeraj Srivastava2
  • Ajit Kumar Srivastava3

1 Student Member IEEE, School of Computer Science and Engineering Vellore Institute of Technology, Vellore, India. 2 Senior Member IEEE , Associate Professor, Department of Electronics & Communication Engineering, Rustamji Institute of Technology, BSF Academy Tekanpur Gwalior, India. 3 Associate Professor & Head Department of CSE SIS Tec-R, Bhopal, India.

Article Information

DOI
No DOI
Published Online
May-August 2023
Pages
12-19
Article Type
Research Article
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No DOI available for cross-reference

Abstract

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Cross-site scripting attack, abbreviated as XSS , has been an incessant problem for Web applications since the early 2000s. It is a code injection attack on the client -side where an attacker injects malicious payload intoavulner able we b applic ation, without client’s knowledge. The attacker is often successful in executing the malicious code inadvertently in the browser of an unwary user. Attempts have been made to implement the detection of XS S attacks using Genetic Algorithm, Web Vulnerabilities Finder, Fuzzy Interference Model, but they all come with drawbacks. Implementation URL of the website is collected through an extension and vulnerability is checked by injecting java-script code to the website. If the website is vulnerable, then display a pop -up stating “Website is vulnerable, be aware”, else display a pop -up stating “ W ebsite is not vulner able ”. It is a low cost model which is easy to implement.

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