Lightweight and secure PUF key storage using limits of machine learning
Name
Devadas-Lightweight and secure.pdf
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1.14 MB
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Adobe PDF
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Author(s)
Yu, Meng-Day (Mandel)
M’Raihi, David
Sowell, Richard
Devadas, Srinivas
Date Issued
September 2011
Journal
Cryptographic Hardware and Embedded Systems – CHES 2011
Publisher
Springer Berlin / Heidelberg
Citation
Yu, Meng-Day et al. “Lightweight and Secure PUF Key Storage Using Limits of Machine Learning.” Cryptographic Hardware and Embedded Systems – CHES 2011. Ed. Bart Preneel & Tsuyoshi Takagi. LNCS Vol. 6917. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. 358–373.
Version
Author's final manuscript
Abstract
A lightweight and secure key storage scheme using silicon Physical Unclonable Functions (PUFs) is described. To derive stable PUF bits from chip manufacturing variations, a lightweight error correction code (ECC) encoder / decoder is used. With a register count of 69, this codec core does not use any traditional error correction techniques and is 75% smaller than a previous provably secure implementation, and yet achieves robust environmental performance in 65nm FPGA and 0.13μ ASIC implementations. The security of the syndrome bits uses a new security argument that relies on what cannot be learned from a machine learning perspective. The number of Leaked Bits is determined for each Syndrome Word, reducible using Syndrome Distribution Shaping. The design is secure from a min-entropy standpoint against a machine-learning-equipped adversary that, given a ceiling of leaked bits, has a classification error bounded by ε. Numerical examples are given using latest machine learning results.
Description
13th International Workshop, Nara, Japan, September 28 – October 1, 2011. Proceedings
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1007/978-3-642-23951-9_24
