Entropy of Audio Fingerprints for Unobtrusive Device Authentication

نویسندگان

  • Stephan Sigg
  • Matthias Budde
  • Yusheng Ji
  • Michael Beigl
چکیده

Context-based authentication methods enable the unobtrusive establishment of authentication or even secure keys. While several context-based authentication methods have been proposed recently, often the entropy of the seed for the cryptographic keys is not exploited. We study the entropy of audio fingerprints which can be utilized to pair devices in close proximity. In this work, for 600 audio fingerprints from five distinct audio classes recorded at three different locations, we applied 7490 statistical tests from the dieHarder battery of statistical tests.

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تاریخ انتشار 2011