Breaking through fixed PUF block limitations with differential sequence coding and convolutional codes

Abstract

Secret key generation with Physical Unclonable Functions (PUFs) is an alternative to conventional secure key storage with non-volatile memory. In a PUF, secret bits are generated by evaluating the internal state of a physical source. Typically, error correction is applied in two stages to remove the instability in the measurement that is caused by environmental influences. We present a new syndrome coding scheme, called Differential Sequence Coding (DSC), for the first error correction stage. DSC applies a fixed reliability criterion and searches the PUF output sequence sequentially until a number of suitable PUF outputs is found. This permits to guarantee the reliability of the indexed PUF outputs. Our analysis demonstrates that DSC is information theoretically secure and highly efficient. To the best of our knowledge, we are the first to propose a convolutional code with Viterbi decoder as second stage error correction for PUFs. We adapt an existing bounding technique for the output bit error probability to our scenario to make reliability statements without the need of laborious simulations. Aiming for a low implementation overhead in hardware, a serialized low complexity FPGA implementation of DSC and the Viterbi decoder is used in this work. For a reference SRAM PUF scenario, PUF size is reduced by 20% and the helper data size decreases by over 40% compared to the best referenced FPGA implementations in each class with a minor increase in the number of slices.