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。然而，一旦被迫披露加密密钥，明文就会立即泄露给强大的对手。压迫性政权越来越多地采取这种强制披露的做法，以积极审查和过滤网络，定期调查和监禁记者和人权活动家，并通常激烈反对向外部世界提供任何妥协信息。这项工作的核心问题往往是记者、人权活动家、举报人和公民个人的生死问题。试图解决这个问题的现有系统在现实对手面前崩溃，这些对手可以在多个时间点访问存储介质（“多快照”对手）。这项工作将设计和建立强有力的安全高度实用的似是而非的可否认的存储机制，是强大的对多快照的对手，使用户能够合理地拒绝拥有某些数据，即使对手有机会访问用户的存储设备和凭据。该项目的研究成果将纳入本科和研究生课程，并将有助于培训下一代劳动力的合理否认范式和技术。合理否认对于人权活动家，压迫政权中的举报人以及关注隐私权的公民至关重要，因为它可能是在越来越多的控制，监督和审查的世界中确保个人隐私的唯一手段。这项工作将推进对广泛的存储系统和媒体的合理否认的基本理解。它将结合联合收割机不同的技术，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、用于加强系统堆栈中的可否认性的可信执行环境以及用于解决覆盖流量信息的机器学习，以提供强大的可否认存储系统。它将构建多个系统，供公众使用，并集成到主流操作系统中。这项工作还将通过设计，建造并展示了世界上第一个“防窥探”的信号加密智能手机消息应用程序，从而击败能够强迫用户透露加密密钥的对手。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响力进行评估，被认为值得支持审查标准。

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