Modeling and Analysis of SRAM PUF Bias Patterns in 14nm and 7nm FinFET Technology Nodes
S. Masoumian (Intrinsic ID B.V., TU Delft - Computer Engineering)
Roel Maes (Intrinsic ID B.V.)
Rui Wang (Intrinsic ID B.V.)
Karthik Keni Yerriswamy (Intrinsic ID B.V.)
Geert-Jan Schrijen (Intrinsic ID B.V.)
Said Hamdioui (TU Delft - Computer Engineering)
M. Taouil (TU Delft - Computer Engineering)
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Abstract
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.