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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16287
Title: Robust injection point-based framework for modern applications against XSS vulnerabilities in online social networks
Authors: Gupta, Shashank
Keywords: Computer Science
Injection points
Script injection vulnerabilities
Cross-site scripting attack
Context-sensitive sanitisation
Document object model tree
Issue Date: May-2018
Publisher: Inder Science
Abstract: The authors introduced a universal and an automated server-side flexible framework, XSS-explorer, which automatically scrutinises the web applications in order to discover XSS attack vectors. XSS-explorer is capable enough for exploring and recognising all the injection points of web application and produces explicit XSS attack injection investigations for all such injection points. Our approach is based on methods permitting precise filling of injection points of forms with usable info. The identification of such injection points permits our technique to retrieve each possible web page of application, allowing a wider exploration and accelerating the discovery frequency of XSS attack vectors. We evaluate efficiency of our scheme on a suite of open source multimedia applications by applying F-test hypothesis and F-measure. These evaluations indorse that precise filling of the injection points by only usable info confirms an enhanced efficiency of the tests, thus accelerating the recognition rate of XSS attacks.
URI: https://www.inderscienceonline.com/doi/abs/10.1504/IJICS.2018.091455
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16287
Appears in Collections:Department of Computer Science and Information Systems

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