  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.
