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.

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