Modeling and Analysis of SRAM PUF Bias Patterns in 14nm and 7nm FinFET Technology Nodes

被引:0
|
作者
Masoumian, Shayesteh [1 ]
Maes, Roel [1 ]
Wang, Rui [1 ]
Yerriswamy, Karthik Keni [1 ]
Schrijen, Geert-Jan [1 ]
Hamdioui, Said [2 ]
Taouil, Mottaqiallah [2 ]
机构
[1] Intrins ID BV, Eindhoven, Netherlands
[2] Delft Univ Technol, Fac EE Math & CS, Delft, Netherlands
来源
2023 IFIP/IEEE 31ST INTERNATIONAL CONFERENCE ON VERY LARGE SCALE INTEGRATION, VLSI-SOC | 2023年
关键词
Bias; FinFET; Power Supply Network; SRAM PUF; Temperature; CELL;
D O I
10.1109/VLSI-SoC57769.2023.10321895
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
SRAM Physical Unclonable Functions (PUFs) are one of the popular forms of PUFs that can be used to generate unique identifiers and randomness for security purposes. Hence, their resilience to attacks is crucial. The probability of attacks increases when the SRAM PUF start-up values follow a predictable pattern which we refer to as bias. In this paper, we investigate the parameters impacting the SRAM PUF bias of advanced FinFET SRAM designs. In particular, we analyze the bias with respect to temperature, mismatches in the power supply network, and ramp-up time. We also consider process variation, circuit noise, and SRAM layout in our analysis. Our simulations results match with the silicon measurements. From the experiments we conclude that (i) the SRAM layout and in particular the power supply network can lead to a bias, (ii) this bias increases with temperature, and (iii) this bias increases when the supply ramp-up time decreases.
引用
收藏
页码:171 / 176
页数:6
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