Weak and Strong SRAM cells analysis in embedded memories for PUF applications

Alheyasat, A.; Torrens, Gabriel; Bota, S.A.; Alorda, B.

doi:10.1109/dcis201949030.2019.8959939

Cited by 7 publications

(2 citation statements)

References 5 publications

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“…They provided some procedures for better data collection. Alheyasat et al, [35] performed the mismatch factor analysis on different PUFs and proved the viability of a robust PUF bit selection method.…”

Section: Previous Workmentioning

confidence: 99%

Data Remanence Based Approach towards Stable Key Generation from Physically Unclonable Function Response of Embedded SRAMs using Binary Search

Pyi Phyo Aung,

Nordinah Ismail,

Chia Yee Ooi

et al. 2023

ARASET

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Today’s device authentications in IoT devices use public and private key cryptography. Nevertheless, they are still vulnerable to threats because keys or device IDs digitally stored in IoT devices can be stolen or cloned. In contrast, SRAM PUFs utilize physical variations in memory cells of embedded SRAM in microcontrollers or standalone SRAM chips. These inherent physical characteristics are unpredictable and practically impossible to duplicate. They are negligible to affect regular SRAM operation but large enough to be used for authentication purposes in SRAM PUFs operation. However, SRAM PUFs have poor stability and a relatively high bit error rate (BER). Temporal Majority Voting (TMV) and other error correction codes (ECCs) have improved SRAM PUFs performance, but they require a lot of processing time and hardware resources. The data remanence nature of SRAM cells can be utilized to select SRAM PUFs bits with much lower BER and more stable bits, but a suitable algorithm is required to find the best possible power-off time for each type of chip. This paper proposes using the data remanence method and binary search algorithm to obtain the strong SRAM PUFs characteristics of the selected SRAMs at the optimal power-off time. These SRAMs include embedded SRAMs of AtMega328P, STM32F108C, ESP8266 microcontrollers, and an off-the-shelf SRAM chip 23LC1024-I/P, which are being used in various IoT applications. The strong SRAM PUF has more stable characteristics that reduce BER to 0% and increase stability to 99.999%. This proposed method can be utilized on any IoT platform which deals with essential data and requires less resource-hungry security and authentication protocols.

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Section: Previous Workmentioning

confidence: 99%

Data Remanence Based Approach towards Stable Key Generation from Physically Unclonable Function Response of Embedded SRAMs using Binary Search

Pyi Phyo Aung,

Nordinah Ismail,

Chia Yee Ooi

et al. 2023

ARASET

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“…Choosing the memory cells with the highest mismatch will lead to more repeatable and dependable SRAM-PUF fingerprint. This paper deals with the mismatch metric (MF) introduced in [13] as a predictor for SRAM memory cells SUV. The metric intended to be used at identifying those SRAM cells with the most repeatable start-up values, and thus better candidates for PUFs.…”

Section: Mismatch-based Metricmentioning

confidence: 99%

Estimation during Design Phases of Suitable SRAM Cells for PUF Applications Using Separatrix and Mismatch Metrics

et al. 2021

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Physically unclonable functions (PUFs) are used as low-cost cryptographic primitives in device authentication and secret key creation. SRAM-PUFs are well-known as entropy sources; nevertheless, due of non-deterministic noise environment during the power-up process, they are subject to low challenge-response repeatability. The dependability of SRAM-PUFs is usually accomplished by combining complex error correcting codes (ECCs) with fuzzy extractor structures resulting in an increase in power consumption, area, cost, and design complexity. In this study, we established effective metrics on the basis of the separatrix concept and cell mismatch to estimate the percentage of cells that, due to the effect of variability, will tend to the same initial state during power-up. The effects of noise and temperature in cell start-up processes were used to validate the proposed metrics. The presented metrics may be applied at the SRAM-PUF design phases to investigate the impact of different design parameters on the percentage of reliable cells for PUF applications.

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Selection of SRAM Cells to improve Reliable PUF implementation using Cell Mismatch Metric

Alheyasat

Torrens

Bota

et al. 2020

2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS)

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Weak and Strong SRAM cells analysis in embedded memories for PUF applications

Cited by 7 publications

References 5 publications

Data Remanence Based Approach towards Stable Key Generation from Physically Unclonable Function Response of Embedded SRAMs using Binary Search

Data Remanence Based Approach towards Stable Key Generation from Physically Unclonable Function Response of Embedded SRAMs using Binary Search

Estimation during Design Phases of Suitable SRAM Cells for PUF Applications Using Separatrix and Mismatch Metrics

Selection of SRAM Cells to improve Reliable PUF implementation using Cell Mismatch Metric

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