Research on Strong-association Rule Based Web Application Vulnerability Detection

Abstract—With the increase of the web applications in
information society, web application software security
become more and more important. Recent investigations
show that web application vulnerabilities have become the
largest security threat. Websense security report shows that
in the first half of year 2008 above 75% of the most popular
web site have utilized by the hackers to run malicious code.
Detecting and solving vulnerability is the effective way to
enhance web security. In this paper we focus on the
regression test in web vulnerability detection, and present a
strong-association rule based algorithm to make the
detection more efficient. In the first step we traverse the
whole web site to get the web page collection. And then, in
the regression test, we make the association between the
pages and expand the pages to a collection set. The set will
used in the following iterate traverse. And we define the
relational grade to describe the association. Finally, we do
the experiment on our target web site which contains the
known vulnerabilities such as XSS and SQL injection, and
the result shows that the algorithm can detect almost all the
pages that may contains vulnerabilities in the target web
Keywords- Web security testing; Web vulnerability; Strong
association Rule


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Category: Research Paper | Added by: as (2020-11-17)
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