SaTC: CORE: Small: Efficient Plausible Deniability Systems

SaTC：核心：小型：高效的合理推诿系统

• 批准号: 2052951
• 负责人: Radu Sion
• 金额: $ 49.97万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2052951&HistoricalAwards=false
• 关键词: SaTC; CORE; Small; Efficient; Plausible

Data privacy is essential in today’s computing-infused societal structures. Encryption is usually the first line of defense against privacy violations. However, upon compelled disclosure of encryption keys plaintexts are immediately revealed to powerful adversaries. Oppressive regimes increasingly practice such forced disclosure to actively censor and filter networks, routinely investigate and imprison journalists and rights activists, and generally fight fiercely against any compromising information being presented to the outside world. The problem at the heart of this work is often a matter of life and death to journalists, human rights activists, whistleblowers, and individual citizens Existing systems that tries to address this problem, break down in the presence of realistic adversaries that can access the storage media at multiple points in time (“multi-snapshot” adversary). This work will design and build strongly secure highly practical plausible deniable storage mechanisms that are robust against a multi-snapshot adversary enabling users to plausibly deny the possession of certain data even when the adversary has access to the user storage devices and credentials. Research results from this project would be incorporated into both undergraduate and graduate level courses and would help train the next generation workforce in plausible deniability paradigm and technology. Plausible deniability is vital for human rights activists, whistleblowers in oppressive regimes, and citizens concerned about privacy as a right, since it is perhaps the only remaining recourse to ensuring personal privacy in a world of increasing control, oversight, and censorship.This work will advance the foundational understanding of plausible deniability across a broad swath of storage systems and media. It will combine different technology, such as, faster access privacy mechanisms, data encoding mechanisms using write-once memory, trusted execution environments to harden deniability in the system stack and machine learning for addressing cover traffic information, to provide a robust plausibly deniable storage system. It will build multiple systems that will be released for public use and integrated into mainstream operating systems. The work will also show the wide-ranging implications of strongly secure plausible deniability mechanisms by designing, building and demonstrating the world’s first “snoop-proof” Signal encrypted smartphone messaging application thereby defeating adversaries able to coerce users to reveal encryption keys.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

数据隐私在当今充满计算的社会结构中至关重要，加密通常是防止侵犯隐私的第一道防线，但是，在强制披露加密密钥后，明文会立即暴露给强大的对手，从而越来越多地实行这种强制披露以进行主动审查。和过滤网络，定期调查和监禁记者和维权人士，并普遍强烈反对向外界提供的任何有损信息。这项工作的核心问题往往是记者的生死攸关的问题和人权问题。活动家、举报人和公民个人试图解决这个问题的现有系统，在存在可以在多个时间点访问存储介质的现实对手（“多快照”对手）的情况下崩溃了。这项工作将设计和构建。安全的、高度实用的合理可拒绝存储机制，对于多快照对手来说是稳健的，即使对手有权访问用户存储设备和凭证，用户也能够合理地拒绝拥有某些数据。该项目将纳入本科生和研究生课程，并有助于培训下一代劳动力合理的否认范式和技术对于人权活动家、压迫政权的举报者以及关注隐私权的公民至关重要。在控制、监督和审查日益加强的世界中，这可能是确保个人隐私的唯一手段。这项工作将促进对广泛的存储系统和媒体的合理推诿的基本理解。它将结合不同的存储系统和媒体。技术，例如更快的访问隐私机制、使用一次写入存储器的数据编码机制、强化系统堆栈中的可否认性的可信执行环境以及用于寻址覆盖流量信息的机器学习，将构建一个强大的可信可否认的存储系统。这项工作还将通过设计、构建和演示世界上第一个“防窥探”信号加密智能手机消息传递，展示安全可信推诿机制的广泛影响。应用程序击败能够强迫用户泄露加密密钥的对手。该奖项反映了 NSF 的法定使命，并且通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

PEARL: Plausibly Deniable Flash Translation Layer using WOM coding

• 发表时间: 2020-09
• 作者: Chen Chen-Chen;Anrin Chakraborti;R. Sion

SoK: Plausibly Deniable Storage

SoK：合理可否认的存储

• DOI: 10.2478/popets-2022-0039
• 发表时间: 2022
• 期刊: Proceedings on Privacy Enhancing Technologies
• 作者: Chen Chen, Xiao Liang