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Designing a XSS Defensive Framework for Web Servers Deployed in the Existing Smart City Infrastructure

Brij B. Gupta, Pooja Chaudhary, Shashank Gupta

Source Title: Journal of Organizational and End User Computing (JOEUC)32(4)

ISSN: 1546-2234|EISSN: 1546-5012|EISBN13: 9781522583714|DOI: 10.4018/JOEUC.2020100105

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MLA

Gupta, Brij B., et al. "Designing a XSS Defensive Framework for Web Servers Deployed in the Existing Smart City Infrastructure." JOEUC vol.32, no.4 2020: pp.85-111. http://doi.org/10.4018/JOEUC.2020100105

APA

Gupta, B. B., Chaudhary, P., & Gupta, S. (2020). Designing a XSS Defensive Framework for Web Servers Deployed in the Existing Smart City Infrastructure. Journal of Organizational and End User Computing (JOEUC), 32(4), 85-111. http://doi.org/10.4018/JOEUC.2020100105

Chicago

Gupta, Brij B., Pooja Chaudhary, and Shashank Gupta. "Designing a XSS Defensive Framework for Web Servers Deployed in the Existing Smart City Infrastructure," Journal of Organizational and End User Computing (JOEUC) 32, no.4: 85-111. http://doi.org/10.4018/JOEUC.2020100105

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Abstract

Cross-site scripting is one of the notable exceptions effecting almost every web application. Hence, this article proposed a framework to negate the impact of the XSS attack on web servers deployed in one of the major applications of the Internet of Things (IoT) i.e. the smart city environment. The proposed framework implements 2 approaches: first, it executes vulnerable flow tracking for filtering injected malicious scripting code in dynamic web pages. Second, it accomplished trusted remark generation and validation for unveiling any suspicious activity in static web pages. Finally, the filtered and modified webpage is interfaced to the user. The prototype of the framework has been evaluated on a suite of real-world web applications to detect XSS attack mitigation capability. The performance analysis of the framework has revealed that this framework recognizes the XSS worms with very low false positives, false negatives and acceptable performance overhead as compared to existent XSS defensive methodologies.