• Medientyp: E-Artikel
  • Titel: DataLair: Efficient Block Storage with Plausible Deniability against Multi-Snapshot Adversaries
  • Beteiligte: Chakraborti, Anrin; Chen, Chen; Sion, Radu
  • Erschienen: Privacy Enhancing Technologies Symposium Advisory Board, 2017
  • Erschienen in: Proceedings on Privacy Enhancing Technologies, 2017 (2017) 3, Seite 179-197
  • Sprache: Englisch
  • DOI: 10.1515/popets-2017-0035
  • ISSN: 2299-0984
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: Abstract Sensitive information is present on our phones, disks, watches and computers. Its protection is essential. Plausible deniability of stored data allows individuals to deny that their device contains a piece of sensitive information. This constitutes a key tool in the fight against oppressive governments and censorship. Unfortunately, existing solutions, such as the now defunct TrueCrypt [5], can defend only against an adversary that can access a user’s device at most once (“single-snapshot adversary”). Recent solutions have traded significant performance overheads for the ability to handle more powerful adversaries able to access the device at multiple points in time (“multi-snapshot adversary”). In this paper we show that this sacrifice is not necessary. We introduce and build DataLair1, a practical plausible deniability mechanism. When compared with existing approaches, DataLair is two orders of magnitude faster for public data accesses, and 5 times faster for hidden data accesses. An important component in DataLair is a new write-only ORAM construction which improves on the complexity of the state of the art write-only ORAM by a factor of O(logN), where N denotes the underlying storage disk size.
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