对多层应用程序的隐私需求规范进行正式分析

T. Breaux, Ashwini Rao
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引用次数: 45

摘要

公司需要来自多个来源的数据来开发新的信息系统,如社交网络、电子商务和基于位置的服务。系统依赖于复杂的、多方利益相关者的数据供应链来提供价值。这些数据供应链具有复杂的隐私要求:影响多个利益相关者(例如用户、开发人员、公司、政府)的隐私政策规范了多个司法管辖区(例如加利福尼亚、美国、欧洲)的数据收集、使用和共享。监管机构越来越希望公司确保公司隐私政策和公司数据实践之间的一致性。为了解决这个问题,我们提出了一种方法,将自然语言中的策略需求映射到描述逻辑中的形式化表示。使用形式化表示,我们可以对数据供应链中单个策略内和多个策略之间的冲突需求进行推理。此外,我们支持在供应链中跟踪数据流。我们的方法来源于Facebook平台政策的探索性案例研究。我们通过对Facebook、Zynga和aol广告政策的评估,证明了我们方法的可行性。我们的研究结果表明,Facebook和Zynga的政策存在三个冲突,AOL的广告政策存在一个冲突。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Formal analysis of privacy requirements specifications for multi-tier applications
Companies require data from multiple sources to develop new information systems, such as social networking, e-commerce and location-based services. Systems rely on complex, multi-stakeholder data supply-chains to deliver value. These data supply-chains have complex privacy requirements: privacy policies affecting multiple stakeholders (e.g. user, developer, company, government) regulate the collection, use and sharing of data over multiple jurisdictions (e.g. California, United States, Europe). Increasingly, regulators expect companies to ensure consistency between company privacy policies and company data practices. To address this problem, we propose a methodology to map policy requirements in natural language to a formal representation in Description Logic. Using the formal representation, we reason about conflicting requirements within a single policy and among multiple policies in a data supply chain. Further, we enable tracing data flows within the supply-chain. We derive our methodology from an exploratory case study of Facebook platform policy. We demonstrate the feasibility of our approach in an evaluation involving Facebook, Zynga and AOL-Advertising policies. Our results identify three conflicts that exist between Facebook and Zynga policies, and one conflict within the AOL Advertising policy.
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