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Hunting for DOM-Based XSS vulnerabilities in mobile cloud-based online social network

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dc.contributor.author Gupta, Shashank
dc.date.accessioned 2024-11-05T11:50:11Z
dc.date.available 2024-11-05T11:50:11Z
dc.date.issued 2018-02
dc.identifier.uri https://www.sciencedirect.com/science/article/pii/S0167739X17311068
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16298
dc.description.abstract This article presents a runtime Document Object Model (DOM) tree generator and nested context-aware sanitization based framework that alleviates the DOM-based XSS vulnerabilities from the mobile cloud-based OSN. The frameworks executes in dual mode: offline and online. The offline mode captures all the traces of modules of web applications and transformed such traces into static DOM tree for the extraction of benign script nodes. The legitimate script content embedded in such nodes will be marked in the whitelist of scripts. The online mode detects the injection of untrusted script content in the DOM tree generated at runtime. This was done by usually matching the script content embedded in this DOM tree with the whitelist of script code generated at offline mode. Any deviation observed in the script content will be marked as the injection of malicious script content in the dynamically generated DOM tree. This mode also identifies the different context of malicious variables embedded in such scripts and consequently executes the process of nested context-sensitive sanitization on them. The prototype of our mobile cloud-based framework was developed in Java and integrated the functionality of its components on iCanCloud simulator by creating different virtual machines with their proper link-to-link connectivity. The experimental testing and performance evaluation of our work was carried out on the open source OSN websites that are integrated in the virtual cloud servers. Evaluation results revealed that our framework is capable enough to detect the injection of untrusted/malicious script in the dynamically generated DOM tree with very low rate of false positives, false negatives and suffer from acceptable performance overhead. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.subject Computer Science en_US
dc.subject Mobile cloud computing en_US
dc.subject Cross-site scripting (XSS) worms en_US
dc.subject JavaScript code injection attacks en_US
dc.subject DOM-Based XSS attacks en_US
dc.subject Document Object Model (DOM) tree en_US
dc.title Hunting for DOM-Based XSS vulnerabilities in mobile cloud-based online social network en_US
dc.type Article en_US


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