• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2015, Volume: 8, Issue: 30, Pages: 1-7

Original Article

Cross-Site Scripting Detection Based on an Enhanced Genetic Algorithm


Software security vulnerabilities have led to many successful attacks on applications, especially web applications, on a daily basis. These attacks, including cross-site scripting, have caused damages for both web site owners and users. Cross-site scripting vulnerabilities are easy to exploit but difficult to mitigate. Many solutions have been proposed for their detection. However, the problem of cross-site scripting vulnerabilities present in web applications still persists. In this paper, we propose to explore an approach based on genetic algorithms that will be able to detect cross-site scripting vulnerabilities in the source code before an application is deployed. The proposed approach is, so far, only implemented and validated on Java-based web applications, although it can be implemented in other programming languages with slight modifications. Initial evaluations have indicated promising results.
Keywords: Cross-Site Scripting, Genetic Algorithm, Software Security, Vulnerability Detection 


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