A Novel Key Generation Method for Group-Based Physically Unclonable Function Designs

Saeed Abdolinezhad; Lukas Zimmermann; Axel Sikora

doi:10.3390/electronics10212597

A Novel Key Generation Method for Group-Based Physically Unclonable Function Designs

Electronics ◽

10.3390/electronics10212597 ◽

2021 ◽

Vol 10 (21) ◽

pp. 2597

Author(s):

Saeed Abdolinezhad ◽

Lukas Zimmermann ◽

Axel Sikora

Keyword(s):

Key Generation ◽

Iot Security ◽

High Entropy ◽

Physically Unclonable Functions ◽

Security Applications ◽

Cryptographic Key Generation ◽

Secret Keys ◽

Novel Method ◽

Cryptographic Key ◽

Optimum Solution

In recent years, physically unclonable functions (PUFs) have gained significant attraction in IoT security applications, such as cryptographic key generation and entity authentication. PUFs extract the uncontrollable production characteristics of different devices to generate unique fingerprints for security applications. When generating PUF-based secret keys, the reliability and entropy of the keys are vital factors. This study proposes a novel method for generating PUF-based keys from a set of measurements. Firstly, it formulates the group-based key generation problem as an optimization problem and solves it using integer linear programming (ILP), which guarantees finding the optimum solution. Then, a novel scheme for the extraction of keys from groups is proposed, which we call positioning syndrome coding (PSC). The use of ILP as well as the introduction of PSC facilitates the generation of high-entropy keys with low error correction costs. These new methods have been tested by applying them on the output of a capacitor network PUF. The results confirm the application of ILP and PSC in generating high-quality keys.

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Rejection Sampling Schemes for Extracting Uniform Distribution from Biased PUFs

IACR Transactions on Cryptographic Hardware and Embedded Systems ◽

10.46586/tches.v2020.i4.86-128 ◽

2020 ◽

pp. 86-128

Author(s):

Rei Ueno ◽

Kohei Kazumori ◽

Naofumi Homma

Keyword(s):

Uniform Distribution ◽

Nonvolatile Memory ◽

Experimental Simulation ◽

Key Generation ◽

Rejection Sampling ◽

Fuzzy Extractor ◽

High Entropy ◽

Sampling Schemes ◽

Physically Unclonable Functions ◽

Cryptographic Key

This paper presents an efficient fuzzy extractor (FE) construction for secure cryptographic key generation from physically unclonable functions (PUFs). The proposed FE, named acceptance-or-rejection (AR)-based FE, utilizes a new debiasing scheme to extract a uniform distribution from a biased PUF response. The proposed debiasing scheme employs the principle of rejection sampling, and can extract a longer debiased bit string compared to those of conventional debiasing schemes. In addition, the proposed AR-based FE is extended to ternary PUF responses (i.e., ternary encoding of a PUF response). These responses can be derived according to cell-wise reliability of the PUF and are promising for extraction of stable and high-entropy responses from common PUFs. The performance of the AR-based Fes is evaluated through an experimental simulation of PUF-based key generation and compared with conventional FEs. We confirm that the proposed AR-based FE can achieve the highest efficiency in terms of PUF and nonvolatile memory (NVM) sizes for various PUF conditions among the conventional counterparts. More precisely, the AR-based FE can realize a 128-bit key generation with up-to 55% smaller PUF size or up-to 72% smaller NVM size than other conventional FEs. In addition, the ternary AR-based FE is up to 55% more efficient than the binary version, and can also achieve up-to 63% higher efficiency than conventional counterparts. Furthermore, we show that the AR-based FE can be applied to PUFs with local biases (e.g., biases depending on cell location in SRAM PUFs), unlike all the conventional schemes, for which only global (or identical) biases are assumed.

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