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

Abstract

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.

Keywords

• Physical unclonable functions
• helper data scheme
• channel capacity