Neuroscience meets cryptography: Designing crypto primitives secure against rubber hose attacks

Hristo Bojinov, Daniel Sanchez, Paul Reber, Dan Boneh, Patrick Lincoln

Research output: Contribution to conferencePaperpeer-review

41 Scopus citations

Abstract

Cryptographic systems often rely on the secrecy of cryptographic keys given to users. Many schemes, however, cannot resist coercion attacks where the user is forcibly asked by an attacker to reveal the key. These attacks, known as rubber hose cryptanalysis, are often the easiest way to defeat cryptography. We present a defense against coercion attacks using the concept of implicit learning from cognitive psychology. Implicit learning refers to learning of patterns without any conscious knowledge of the learned pattern. We use a carefully crafted computer game to plant a secret password in the participant’s brain without the participant having any conscious knowledge of the trained password. While the planted secret can be used for authentication, the participant cannot be coerced into revealing it since he or she has no conscious knowledge of it. We performed a number of user studies using Amazon’s Mechanical Turk to verify that participants can successfully re-authenticate over time and that they are unable to reconstruct or even recognize short fragments of the planted secret.

Original languageEnglish (US)
Pages129-141
Number of pages13
StatePublished - Jan 1 2012
Event21st USENIX Security Symposium - Bellevue, United States
Duration: Aug 8 2012Aug 10 2012

Conference

Conference21st USENIX Security Symposium
Country/TerritoryUnited States
CityBellevue
Period8/8/128/10/12

Funding

We would like to thank all the paid volunteers who have contributed to our user studies through their participation. This work was funded by NSF and a MURI grant.

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Safety, Risk, Reliability and Quality

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