  We address security and privacy problems for digital devices and biometrics
from an information-theoretic optimality perspective, where a secret key is
generated for authentication, identification, message encryption/decryption, or
secure computations. A physical unclonable function (PUF) is a promising
solution for local security in digital devices and this review gives the most
relevant summary for information theorists, coding theorists, and signal
processing community members who are interested in optimal PUF constructions.
Low-complexity signal processing methods such as transform coding that are
developed to make the information-theoretic analysis tractable are discussed.
The optimal trade-offs between the secret-key, privacy-leakage, and storage
rates for multiple PUF measurements are given. Proposed optimal code
constructions that jointly design the vector quantizer and error-correction
code parameters are listed. These constructions include modern and algebraic
codes such as polar codes and convolutional codes, both of which can achieve
small block-error probabilities at short block lengths, corresponding to a
small number of PUF circuits. Open problems in the PUF literature from a signal
processing, information theory, coding theory, and hardware complexity
perspectives and their combinations are listed to stimulate further
advancements in the research on local privacy and security.
