SFB 1223: Methods and Tools for Understanding and Controlling Privacy

互联网已经成为一个全球性的多媒体平台，数十亿用户越来越多地在其中度过他们生活的大部分时间。在这种情况下，终端用户的在线隐私在很大程度上是一个未解决的问题。网络数据的广泛流通、易于获取和永久性带来了从公开尴尬到申请工作或保险时不利的风险。新的商业模式已经出现，以前所未有的方式跟踪和货币化个人信息。立法者已经开始通过收紧隐私法规来应对，但我们可以说缺乏完全遵守这些法规的技术，用户也缺乏对做出知情隐私选择的支持。为提供在线隐私建立一个全面的科学基础是一项长期的努力，需要广泛涵盖两个中心研究领域的基础研究工作：理解隐私，即如何识别互联网上的隐私敏感信息并评估有害的隐私后果；和控制隐私，即…鉴于当今数字环境和新兴技术的动态变化，如何强制执行用户隐私要求。CRC将为解决这些问题做出概念上和实际上的贡献，包括，例如，评估公共视觉数据潜在隐私威胁的图像分析方法，在复杂的移动传感和记录设备存在下保护隐私的技术，以及在不抑制其功能的情况下保持用户在线交互匿名的解决方案。三个工作小组将促进跨领域主题的联合研究：数据模型的综合框架，作为不同类型的隐私分析和执法之间相互作用的基础；不同隐私观念的相互影响；以及一个方法框架来促进我们解决方案的可用性。实现我们的目标远远超出了传统的安全和隐私研究。它需要结合自上而下的研究方法，这对于理解开放世界和现有基础设施中的隐私是必要的；用自下而上的研究方法来控制隐私，完全重塑基础设施，以提供坚定的保障。它需要紧密整合专业知识，并推动广泛的计算机科学子领域的长期合作，包括信息系统、计算机视觉和社交网络分析，以及经典的安全和隐私研究。参与机构在应对这一挑战方面处于独特的地位。从长远来看，我们看到了对研究界的巨大影响：一种范式的转变，一种全面、整体的方法，超越了传统隐私研究与邻近领域之间现有的障碍。

The Internet has become a global multimedia platform in which billions of users increasingly conduct sizable parts of their lives. In this context, online privacy of end-users is a largely unsolved problem. The wide circulation, easy accessibility and permanent nature of online data incurs risks ranging from public embarrassment to disadvantages when applying for jobs or insurance. New business models have emerged, tracking and monetizing personal information in an unprecedented manner. Legislators have started to respond by tightening privacy regulations, but we arguably lack the technology to fully comply with such regulations, and users lack support for making informed privacy choices. Establishing an overarching scientific foundation for providing online privacy is a long-term endeavor, requiring a fundamental research effort broadly covering two central research areas: Understanding Privacy, i.e. how to identify privacy-sensitive information in the Internet and assess the detrimental privacy consequences; and Controlling Privacy, i.e.. how to enforce user privacy demands given the dynamics of present-day digital habitats and emerging technologies. The CRC will make conceptual and tangible contributions addressing these questions, including, for example, image analysis methods that assess the potential privacy threat of public visual data, techniques protecting privacy in the presence of sophisticated mobile sensing and recording devices, and solutions preserving a user¿s anonymity in online interactions without inhibiting their functionality. Three task forces will facilitate joint research on cross-cutting themes: a comprehensive framework for data models as a basis for the interaction between different kinds of privacy analysis and enforcement; the interplay of different privacy notions; and a methodological framework to foster the usability of our solutions.Achieving our goals goes far beyond traditional security and privacy research. It requires to combinetop-down research approaches, necessary to understand privacy in an open world and on existing infrastructures; with bottom-up research approaches that are necessary to control privacy and completely reshape infrastructures in order to provide firm guarantees. It requires to tightly integrate the expertise from, and drive the long-term collaboration of, a wide range of computer science subareas ¿ including, e.g., information systems, computer vision, and social networks analysis ¿ with classical security & privacy research. The participating institutions are in a unique position to tackle this challenge. On the long run, we see a great impact on our research community: a paradigm shift towards a comprehensive, holistic approach that surmounts existing barriers between traditional privacy research and adjacent areas.