Cryptology ePrint Archive: Report 2021/1547

SoK: Plausibly Deniable Storage

Chen Chen and Xiao Liang and Bogdan Carbunar and Radu Sion

Abstract: Data privacy is critical in instilling trust and empowering the societal pacts of modern technology-driven democracies. Unfortunately, it is under continuous attack by overreaching or outright oppressive governments, including some of the world's oldest democracies. Increasingly-intrusive anti-encryption laws severely limit the ability of standard encryption to protect privacy. New defense mechanisms are needed. Plausible deniability (PD) is a powerful property, enabling users to hide the existence of sensitive information in a system under direct inspection by adversaries. Popular encrypted storage systems such as TrueCrypt and other research efforts have attempted to also provide plausible deniability. Unfortunately, these efforts have often operated under less well-defined assumptions and adversarial models. Careful analyses often uncover not only high overheads but also outright security compromise. Further, our understanding of adversaries, the underlying storage technologies, as well as the available plausible deniable solutions have evolved dramatically in the past two decades. The main goal of this work is to systematize this knowledge. It aims to: - identify key PD properties, requirements, and approaches; - present a direly-needed unified framework for evaluating security and performance; - explore the challenges arising from the critical interplay between PD and modern system layered stacks; - propose a new "trace-oriented" PD paradigm, able to decouple security guarantees from the underlying systems and thus ensure a higher level of flexibility and security independent of the technology stack. This work is meant also as a trusted guide for system and security practitioners around the major challenges in understanding, designing, and implementing plausible deniability into new or existing systems.

Category / Keywords: applications / Plausible Deniability, Storage, Censorship

Original Publication (in the same form): Proceedings of the 22nd Privacy Enhancing Technologies Symposium (PETS 2022)

Date: received 24 Nov 2021

Contact author: xiao crypto at gmail com

Available format(s): PDF | BibTeX Citation

Version: 20211129:121808 (All versions of this report)

Short URL: ia.cr/2021/1547


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