JPrivacy: A java privacy profiling framework for Big Data applications

Mohamed Abdellatif, Iman Saleh, M. Blake
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Abstract

Businesses and government agencies are continuously generating and collecting huge amounts of data and building related Big Data applications. Big Data applications involve the collaborative integration of APIs from different providers. A challenge in this domain is to guarantee the conformance of the integration to privacy terms and regulations. In this paper, we present JPrivacy, a privacy profiling framework for Big Data applications. JPrivacy proposes a model for privacy rules and provide the algorithms and related tools to check Java code against these rules. We show through experimentation that JPrivacy can effectively detect privacy violations by statically analyzing a piece of code.
JPrivacy:大数据应用的java隐私分析框架
企业和政府机构不断产生和收集大量数据,并构建相关的大数据应用。大数据应用涉及来自不同提供商的api的协作集成。该领域的一个挑战是保证集成符合隐私条款和法规。在本文中,我们介绍了JPrivacy,一个用于大数据应用的隐私分析框架。JPrivacy为隐私规则提出了一个模型,并提供了算法和相关工具来根据这些规则检查Java代码。我们通过实验证明,JPrivacy可以通过静态分析一段代码来有效地检测隐私侵犯。
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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