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Reducing Temperature Induced Unreliability in Sub-Threshold Strong PUFs through Circuit Modeling

Due to increased adoption of IoT devices, Physically Unclonable Function (PUF) circuits are essential as a lightweight security primitive. However existing PUFs suffer from imperfect reliability due to environmental variation. In this paper, we propose a PUF-server paradigm in which the server hosts a temperature model of the PUF, and the PUF informs the server of its response, and temperature through an integrated sensor. The model can predict responses for two different strong PUFs across −45°C to 90°C and thus avoids losing challenge-response pairs(CRPs) owing to low mismatch. Simulations show the model-based reliability improves to 97.9% − 99.5% compared with conventional reliability of 83.9% − 86.3%. Conversely, a loss of 25% − 40% of the CRPs is observed in order to improve the conventional reliability to match the model-based reliability. These results are also shown to be robust against quantization errors of a temperature sensor.