Workshop: Theory and Science of Obfuscation as a Methodology for Privacy and Security

研讨会：混淆作为隐私和安全方法的理论和科学

• 批准号: 1642553
• 负责人: Finn Brunton
• 金额: $ 5万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1642553&HistoricalAwards=false
• 关键词: Workshop; Theory; Science; Obfuscation; Methodology

Obfuscation studies how to insert noise into an existing signal to make data or information-stream more ambiguous, confusing, harder to exploit, and more difficult to act on. As an important topic in both privacy/security and information processing, it has been studied from many different perspectives in many related areas, e.g., data privacy, databases, machine learning, ethics, etc. This workshop represents one of the first attempts to consolidate and shape the area as a whole, and help develop a new research community that carries out obfuscation research in a holistic fashion.Specifically, this workshop aims to foster and develop new interdisciplinary research partnerships around obfuscation, by involving researchers, designers, and system producers, including but not limited to academic researchers, industry researchers and practitioners, and independent software producers and privacy activists. The workshop seeks to create benchmarks, assessment tools, and evaluation frameworks for obfuscation techniques, formalizing the notion of obfuscation, and identifying its key challenges and use cases. Through open, online publications, this workshop contributes to the broader conversation about putting obfuscation in practice, and therefore has broader impacts on industry and government, as well as user and developer communities who are interested in producing the next-generation privacy technologies.

模糊处理研究如何在现有信号中插入噪声，使数据或信息流更加模糊、令人困惑、更难利用、更难采取行动。作为隐私/安全和信息处理的一个重要主题，它在许多相关领域从许多不同的角度进行了研究，如数据隐私、数据库、机器学习、伦理学等。这次研讨会是巩固和塑造整个领域的第一次尝试，并帮助开发一个新的研究社区，以整体的方式进行混淆研究。具体地说，本研讨会旨在培养和发展新的围绕混淆的跨学科研究伙伴关系，包括研究人员、设计者和系统制作者，包括但不限于学术研究人员、行业研究人员和从业人员，以及独立软件制作者和隐私权活动家。研讨会旨在为模糊处理技术创建基准、评估工具和评估框架，将模糊处理的概念正式化，并确定其主要挑战和用例。通过开放的在线出版物，该研讨会有助于更广泛地讨论将模糊处理付诸实践，因此对行业和政府以及对生产下一代隐私技术感兴趣的用户和开发人员社区具有更广泛的影响。

项目成果

Obfuscation Workshop Report

混淆研讨会报告

• 发表时间: 2017
• 期刊: Obfuscation Workshop 2017
• 作者: Brunton, Finn;Nissenbaum, Helen;Echizen, Isao;Houmansadr, Amir;Cote, Nicole;Hammond, Rob;Friedler, Sorelle;Pawlick, Jeffrey;Zhu, Quanyan;Ashley, Paul
• 通讯作者: Ashley, Paul