Günlü Onur, Schaefer Rafael
Information Theory and Applications Chair, Technische Universität Berlin, 10623 Berlin, Germany.
Entropy (Basel). 2020 Dec 24;23(1):16. doi: 10.3390/e23010016.
We address security and privacy problems for digital devices and biometrics from an information-theoretic optimality perspective to conduct authentication, message encryption/decryption, identification or secure and private computations by using a secret key. A physical unclonable function (PUF) provides local security to 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 are applied to simplify information-theoretic analyses. The best trade-offs between the privacy-leakage, secret-key, and storage rates are discussed. Proposed optimal 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 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.
我们从信息论最优性的角度探讨数字设备和生物特征识别的安全与隐私问题，以便通过使用密钥进行身份验证、消息加密/解密、识别或安全私密计算。物理不可克隆函数（PUF）为数字设备提供本地安全性，本综述为对最优PUF构造感兴趣的信息论学家、编码理论家及信号处理领域的研究人员提供了最相关的总结。应用低复杂度信号处理方法简化信息论分析。讨论了隐私泄露、密钥和存储速率之间的最佳权衡。列出了联合设计矢量量化器和纠错码参数的最优构造方案。这些构造方案包括诸如极化码和卷积码等现代码和代数码，它们在短码长时都能实现较小的误块率，这对应于少量的PUF电路。从信号处理、信息论、编码理论及硬件复杂度的角度及其组合，列出了PUF文献中的开放性问题，以推动本地隐私和安全研究的进一步发展。
