Design and implementation of robust and low-cost SRAM PUF using PMOS and linear shift register extractor

Gong, Mingyang; Zhang, Haichun; Wang, Chao; Tong, Qiaoling; Liu, Zhenglin

doi:10.1016/j.mejo.2020.104844

Cited by 7 publications

(2 citation statements)

References 7 publications

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“…In [ 86 ], to improve the stability of responses in SRAM PUF, PMOS is added as an SRAM power switch to guarantee an ns-level

(the time it takes for VDDs to increase from zero to a supply voltage VDD) of SRAM cell, which can decrease the power-up time and drop the probability of bit flips. When the chip is powered on, the SRAM power switch is turned on by default.…”

Section: Pufmentioning

confidence: 99%

Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function

Cao

Liu

Lan

et al. 2022

Entropy

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Entropy is a measure of uncertainty or randomness. It is the foundation for almost all cryptographic systems. True random number generators (TRNGs) and physical unclonable functions (PUFs) are the silicon primitives to respectively harvest dynamic and static entropy to generate random bit streams. In this survey paper, we present a systematic and comprehensive review of different state-of-the-art methods to harvest entropy from silicon-based devices, including the implementations, applications, and the security of the designs. Furthermore, we conclude the trends of the entropy source design to point out the current spots of entropy harvesting.

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“…In [ 86 ], to improve the stability of responses in SRAM PUF, PMOS is added as an SRAM power switch to guarantee an ns-level

Section: Pufmentioning

confidence: 99%

Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function

Cao

Liu

Lan

et al. 2022

Entropy

Self Cite

View full text Add to dashboard Cite

show abstract

“…We obtained the PUF reliability [5] parameter to take into account the effect of start-up time and temperature. The considered temperature range was −20 • C to +60 • C and the start-up time was varied more than one order of magnitude according to [37,38]. Results were 97.1% and 98.3% respectively, suggesting that the percentages of cells listed in Table 3, which as stated by [35] correspond to the least influenced by external disturbances, will be largely unaffected by these factors.…”

mentioning

confidence: 99%

SRAM-Based PUF Reliability Prediction Using Cell-Imbalance Characterization in the State Space Diagram

et al. 2022

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This work proposes a methodology to estimate the statistical distribution of the probability that a 6T bit-cell starts up to a given logic value in SRAM memories for PUF applications. First, the distribution is obtained experimentally in a 65-nm CMOS device. As this distribution cannot be reproduced by electrical simulation, we explore the use of an alternative parameter defined as the distance between the origin and the separatrix in the bit-cell state space to quantify the mismatch of the cell. The resulting distribution of this parameter obtained from Monte Carlo simulations is then related to the start-up probability distribution using a two-component logistic function. The reported results show that the proposed imbalance factor is a good predictor for PUF-related reliability estimation with the advantage that can be applied at the early design stages.

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SPUF design based on Camellia encryption algorithm

Chen

Wang

Zhang

et al. 2021

Microelectronics Journal

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Design and implementation of robust and low-cost SRAM PUF using PMOS and linear shift register extractor

Cited by 7 publications

References 7 publications

Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function

Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function

SRAM-Based PUF Reliability Prediction Using Cell-Imbalance Characterization in the State Space Diagram

SPUF design based on Camellia encryption algorithm

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