Physical Unclonable Functions (PUFs) derive unpredictable and device-specific responses from uncontrollable manufacturing variations. While most of the PUFs provide only one response bit per PUF cell, deriving more bits such as a symbol from a higher-order alphabet would make PUF designs more efficient. This type of PUFs is thus suggested in some applications and subject to current research. However, only few methods are available to analyze the statistical performance of such higher-order alphabet PUFs. This work, therefore, introduces various novel schemes. Unlike previous works, the new approaches involve statistical hypothesis testing. This facilitates more refined and statistically significant statements about the PUF regarding bias effects. We utilize real-world PUF data to illustrate the capabilities of the tests. In comparison to state-of-the-art approaches, our methods indeed capture more aspects of bias. Overall, this work is a step towards an improved quality control of higher-order alphabet PUFs.
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Physical Unclonable Functions (PUFs) derive unpredictable and device-specific responses from uncontrollable manufacturing variations. While most of the PUFs provide only one response bit per PUF cell, deriving more bits such as a symbol from a higher-order alphabet would make PUF designs more efficient. This type of PUFs is thus suggested in some applications and subject to current research. However, only few methods are available to analyze the statistical performance of such higher-order alpha...
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