A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
The largest number of cybersecurity attacks is on web applications, in which Cross-Site Scripting (XSS) is the most popular way. The code audit is the main method to avoid the damage of XSS at the source code level. However, there are numerous limits implementing manual audits and rule-based audit tools. In the age of big data, it is a new research field to assist the manual auditing through machine learning. In this paper, we propose a new way to audit the XSS vulnerability in PHP source codedoi:10.3390/app10144740 fatcat:sxfriasfebg7dmdwensjzilnqi