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This thesis addresses security and privacy problems for digital devices and biometrics, where a secret key is generated for authentication, identification, or secure computa- tions. A physical unclonable function (PUF) is a promising solution for local security in digital devices. A low-complexity transform-coding algorithm is developed to make the information-theoretic analysis tractable and motivate a noisy (hidden) PUF source model. The optimal trade-offs between the secret-key, privacy-leakage, and storage rates for multiple measurements of hidden PUFs are characterized. The first optimal and low- complexity code constructions are proposed. Polar codes are designed to achieve the best known rate tuples. The gains from cost-constrained controllable PUF measurements are illustrated to motivate extensions.
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