Maximum-likelihood decoding of device-specific multi-bit symbols for reliable key generation
Author(s)Yu, Meng-Day; Hiller, Matthias; Devadas, Srinivas
MetadataShow full item record
We present a PUF key generation scheme that uses the provably optimal method of maximum-likelihood (ML) detection on symbols derived from PUF response bits. Each device forms a noisy, device-specific symbol constellation, based on manufacturing variation. Each detected symbol is a letter in a codeword of an error correction code, resulting in non-binary codewords. We present a three-pronged validation strategy: i. mathematical (deriving an optimal symbol decoder), ii. simulation (comparing against prior approaches), and iii. empirical (using implementation data). We present simulation results demonstrating that for a given PUF noise level and block size (an estimate of helper data size), our new symbol-based ML approach can have orders of magnitude better bit error rates compared to prior schemes such as block coding, repetition coding, and threshold-based pattern matching, especially under high levels of noise due to extreme environmental variation. We demonstrate environmental reliability of a ML symbol-based soft-decision error correction approach in 28nm FPGA silicon, covering -65°C to 105°C ambient (and including 125°C junction), and with 128bit key regeneration error probability ≤ 1 ppm.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the 2015 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)
Institute of Electrical and Electronics Engineers (IEEE)
Yu, Meng-Day, Matthias Hiller, and Srinivas Devadas. “Maximum-Likelihood Decoding of Device-Specific Multi-Bit Symbols for Reliable Key Generation.” 2015 IEEE International Symposium on Hardware Oriented Security and Trust (HOST) (May 2015).
Author's final manuscript