A physical unclonable function (PUF), like a fingerprint, exploits manufacturing randomness to endow each physical item with a unique identifier. One primary PUF application is the secure derivation of volatile cryptographic keys using a fuzzy extractor (FE) comprising: 1) a secure sketch and 2) an entropy extractor. Although the entropy extractor can be lightweight, the overhead of the secure sketch responsible for correcting naturally noisy PUF responses is usually high. We observe that, in general, response unreliability with respect to an enrolled reference measurement increases with increasing differences between the in-the-field PUF operating condition and the operating condition used in evaluating the enrolled reference response. For the first time, we exploit such an inadvertent but important observation. In contrast to the conventional single reference response enrollment, we propose enrolling multiple reference responses (MRRs) subject to the same challenge but under multiple distinct operating conditions. The critical observation here is that one of the reference operating conditions is likely to be closer to the operating condition of the field deployed PUF, thus resulting in minimizing the expected unreliability when compared to the single reference under the nominal condition. As a consequence, MRR greatly reduces the demand for the expected number of erroneous bits requiring correction and, subsequently, achieves a significant reduction in the error correction overhead. The significant implementation efficiency gains from the proposed MRR method are demonstrated from software implementations of FEs on batteryless resource constraint computational radio frequency identification devices, where realistic PUF data are collected from intrinsic static random access memory PUFs.
A reverse fuzzy extractor is beneficial in reducing the implementation overhead of a PUF key generator on a resource limited token. Mutual authentication based on RFE is firstly proposed by Van Herrewege @cite_21 , later improved by Maes @cite_39 . In Fig. , it depicts the RFE-based mutual authentication protocol in @cite_39 . Notably, the gray shaded secure key @math Hash ( @math ) in Fig. is not explicitly utilized in @cite_39 , instead @math itself is treated as a shared key between the server and the token. Here, instead of using the response @math that might not be uniformly distributed---not having full bit entropy---we adopt the hash function Hash() to extract key sk with full bit-entropy.
@cite_21 @cite_39
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RFID-based tokens are increasingly used in electronic payment and ticketing systems for mutual authentication of tickets and terminals. These systems typically use cost-effective tokens without expensive hardware protection mechanisms and are exposed to hardware attacks that copy and maliciously modify tokens. Physically Unclonable Functions (PUFs) are a promising technology to protect against such attacks by binding security critical data to the physical characteristics of the underlying hardware. However, existing PUF-based authentication schemes for RFID do not support mutual authentication, are often vulnerable to emulation and denial-of service attacks, and allow only for a limited number of authentications. Physically unclonable functions (PUFs) are innovative physical security primitives that produce unclonable and inherent instance-specific measurements of physical objects; in many ways they are the inanimate equivalent of biometrics for human beings. Since they are able to securely generate and store secrets, they allow us to bootstrap the physical implementation of an information security system. In this book the author discusses PUFs in all their facets: the multitude of their physical constructions, the algorithmic and physical properties which describe them, and the techniques required to deploy them in security applications. The author first presents an extensive overview and classification of PUF constructions, with a focus on so-called intrinsic PUFs. He identifies subclasses, implementation properties, and design techniques used to amplify submicroscopic physical distinctions into observable digital response vectors. He lists the useful qualities attributed to PUFs and captures them in descriptive definitions, identifying the truly PUF-defining properties in the process, and he also presents the details of a formal framework for deploying PUFs and similar physical primitives in cryptographic reductions. The author then describes a silicon test platform carrying different intrinsic PUF structures which was used to objectively compare their reliability, uniqueness, and unpredictability based on experimental data. In the final chapters, the author explains techniques for PUF-based entity identification, entity authentication, and secure key generation. He proposes practical schemes that implement these techniques, and derives and calculates measures for assessing different PUF constructions in these applications based on the quality of their response statistics. Finally, he presents a fully functional prototype implementation of a PUF-based cryptographic key generator, demonstrating the full benefit of using PUFs and the efficiency of the processing techniques described. This is a suitable introduction and reference for security researchers and engineers, and graduate students in information security and cryptography.