A New Helper Data Scheme for Soft-Decision Decoding of Binary Physical Unclonable Functions

Physical unclonable functions (PUFs) exploit randomness in the hardware for the derivation of cryptographic keys. In the literature, usually the readout is two-level quantized and hard-decision channel decoding is used to stabilize the extracted key. In this paper, we assess soft-decision decoding of binary PUFs. It is well known in the literature on channel coding that soft-decision decoding provides significant gains over hard-decision decoding since reliability information about the symbols is utilized. The PUF readout process is interpreted as digital transmission over a noisy channel, the respective capacity is calculated, and the optimum decoding metric is derived. In addition, we propose an augmented helper data scheme which is suited for soft-decision decoding. This scheme utilizes the fact that operations on the analog readout values are possible, opposed to operations on hard-decided binary symbols in classical PUFs. The security of the new scheme is proven and a possible realization is discussed. The performance is covered by numerical simulations and by applying the scheme to measurement data from FPGA implementations of ring oscillator PUFs.