Nested context-aware sanitisation and feature injection in clustered templates of JavaScript worms on the cloud-based OSN

Shashank Gupta, B. Gupta, Pooja Chaudhary
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Abstract

This article presents an enhanced JavaScript feature-injection based framework that obstructs the execution of cross-site scripting (XSS) worms from the virtual machines of cloud-based online social network (OSN). It calculates the features of clustered-sanitised compressed templates of JavaScript attack vectors embedded in the HTTP response messages. Any variation observed in such JavaScript feature set indicates the injection of XSS worms on the cloud-based OSN server. The injected worms will further undergo through the process of nested context-aware sanitisation for its safe interpretation on the web browser. The prototype of our framework was developed in Java and installed in the virtual machines of cloud environment. The experimental evaluation of our framework was performed on the platform of OSN-based web applications deployed in the cloud platform. The performance analysis done revealed that our framework detects the injection of malicious JavaScript code with low false negative rate and acceptable performance overhead.
在基于云的OSN上的JavaScript蠕虫集群模板中嵌套上下文感知的清理和特性注入
本文介绍了一个增强的基于JavaScript特性注入的框架,它可以阻止来自基于云的在线社交网络(OSN)的虚拟机的跨站点脚本(XSS)蠕虫的执行。它计算嵌入在HTTP响应消息中的JavaScript攻击向量的聚类净化压缩模板的特性。在这种JavaScript特性集中观察到的任何变化都表明在基于云的OSN服务器上注入了XSS蠕虫。注入的蠕虫将进一步经历嵌套上下文感知的消毒过程,以确保其在web浏览器上的安全解释。我们的框架原型是用Java开发的,并安装在云环境的虚拟机上。我们的框架在部署在云平台的基于osn的web应用程序平台上进行了实验评估。性能分析表明,我们的框架检测恶意JavaScript代码注入,假阴性率低,性能开销可接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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