PUF-Based Authentication

A special issue of Cryptography (ISSN 2410-387X).

Deadline for manuscript submissions: closed (28 February 2018) | Viewed by 50263

Special Issue Editors


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Guest Editor
Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131, USA
Interests: hardware security and trust and design for manufacturability
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Electrical and Computer Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA
Interests: hardware security; design for manufacturability; hardware accelerators; high-performance computing

Special Issue Information

Dear Colleagues,

New hardware architectures for the Internet-of-Things (IoT) are emerging rapidly in response to consumer demands for improved situational awareness, instant access to widely-distributed sources of news and information, and remote, hand-held control over personal assets. Unfortunately, the lessons of the past related to the dangers of adding security and trust as afterthoughts are, once again, beginning to wreak havoc, as the commercial sector forges ahead on delivering poorly-vetted products to market ahead of competitors. A critically important component of IoT security relates to authentication, i.e., confirming the identities of communicating entities, but weak ‘password’ forms of authentication continue to dominate the IoT landscape. This Special Issue focuses on hardware-based authentication of IoT in all of its incarnations, including consumer, industrial Supervisory Control and Data Acquisition (SCADA), automotive, military, and aerospace. Of particular interest are methods and implementations designed to operate in resource-constrained environments, and which can be broadly applied to other challenges, e.g., those related to securing the supply chain.

Prof. Dr. Jim Plusquellic
Dr. Fareena Saqib
Guest Editors

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Keywords

  • IoT
  • authentication
  • resource-constrained
  • hardware security and trust

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Published Papers (4 papers)

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Research

33 pages, 842 KiB  
Article
An Overview of DRAM-Based Security Primitives
by Nikolaos Athanasios Anagnostopoulos, Stefan Katzenbeisser, John Chandy and Fatemeh Tehranipoor
Cryptography 2018, 2(2), 7; https://doi.org/10.3390/cryptography2020007 - 28 Mar 2018
Cited by 21 | Viewed by 14211
Abstract
Recent developments have increased the demand for adequate security solutions, based on primitives that cannot be easily manipulated or altered, such as hardware-based primitives. Security primitives based on Dynamic Random Access Memory (DRAM) can provide cost-efficient and practical security solutions, especially for resource-constrained [...] Read more.
Recent developments have increased the demand for adequate security solutions, based on primitives that cannot be easily manipulated or altered, such as hardware-based primitives. Security primitives based on Dynamic Random Access Memory (DRAM) can provide cost-efficient and practical security solutions, especially for resource-constrained devices, such as hardware used in the Internet of Things (IoT), as DRAMs are an intrinsic part of most contemporary computer systems. In this work, we present a comprehensive overview of the literature regarding DRAM-based security primitives and an extended classification of it, based on a number of different criteria. In particular, first, we demonstrate the way in which DRAMs work and present the characteristics being exploited for the implementation of security primitives. Then, we introduce the primitives that can be implemented using DRAM, namely Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs), and present the applications of each of the two types of DRAM-based security primitives. We additionally proceed to assess the security such primitives can provide, by discussing potential attacks and defences, as well as the proposed security metrics. Subsequently, we also compare these primitives to other hardware-based security primitives, noting their advantages and shortcomings, and proceed to demonstrate their potential for commercial adoption. Finally, we analyse our classification methodology, by reviewing the criteria employed in our classification and examining their significance. Full article
(This article belongs to the Special Issue PUF-Based Authentication)
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4048 KiB  
Article
FPGA Implementation of a Cryptographically-Secure PUF Based on Learning Parity with Noise
by Chenglu Jin, Charles Herder, Ling Ren, Phuong Ha Nguyen, Benjamin Fuller, Srinivas Devadas and Marten Van Dijk
Cryptography 2017, 1(3), 23; https://doi.org/10.3390/cryptography1030023 - 9 Dec 2017
Cited by 20 | Viewed by 14139
Abstract
Herder et al. (IEEE Transactions on Dependable and Secure Computing, 2017) designed a new computational fuzzy extractor and physical unclonable function (PUF) challenge-response protocol based on the Learning Parity with Noise (LPN) problem. The protocol requires no irreversible state updates on the PUFs [...] Read more.
Herder et al. (IEEE Transactions on Dependable and Secure Computing, 2017) designed a new computational fuzzy extractor and physical unclonable function (PUF) challenge-response protocol based on the Learning Parity with Noise (LPN) problem. The protocol requires no irreversible state updates on the PUFs for security, like burning irreversible fuses, and can correct for significant measurement noise when compared to PUFs using a conventional (information theoretical secure) fuzzy extractor. However, Herder et al. did not implement their protocol. In this paper, we give the first implementation of a challenge response protocol based on computational fuzzy extractors. Our main insight is that “confidence information” does not need to be kept private, if the noise vector is independent of the confidence information, e.g., the bits generated by ring oscillator pairs which are physically placed close to each other. This leads to a construction which is a simplified version of the design of Herder et al. (also building on a ring oscillator PUF). Our simplifications allow for a dramatic reduction in area by making a mild security assumption on ring oscillator physical obfuscated key output bits. Full article
(This article belongs to the Special Issue PUF-Based Authentication)
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4743 KiB  
Article
Leveraging Distributions in Physical Unclonable Functions
by Wenjie Che, Venkata K. Kajuluri, Fareena Saqib and Jim Plusquellic
Cryptography 2017, 1(3), 17; https://doi.org/10.3390/cryptography1030017 - 30 Oct 2017
Cited by 4 | Viewed by 9258
Abstract
A special class of Physical Unclonable Functions (PUFs) referred to as strong PUFs can be used in novel hardware-based authentication protocols. Strong PUFs are required for authentication because the bit strings and helper data are transmitted openly by the token to the verifier, [...] Read more.
A special class of Physical Unclonable Functions (PUFs) referred to as strong PUFs can be used in novel hardware-based authentication protocols. Strong PUFs are required for authentication because the bit strings and helper data are transmitted openly by the token to the verifier, and therefore are revealed to the adversary. This enables the adversary to carry out attacks against the token by systematically applying challenges and obtaining responses in an attempt to machine learn, and later predict, the token’s response to an arbitrary challenge. Therefore, strong PUFs must both provide an exponentially large challenge space and be resistant to machine-learning attacks in order to be considered secure. We investigate a transformation called temperature–voltage compensation (TVCOMP), which is used within the Hardware-Embedded Delay PUF (HELP) bit string generation algorithm. TVCOMP increases the diversity and unpredictability of the challenge–response space, and therefore increases resistance to model-building attacks. HELP leverages within-die variations in path delays as a source of random information. TVCOMP is a linear transformation designed specifically for dealing with changes in delay introduced by adverse temperature–voltage (environmental) variations. In this paper, we show that TVCOMP also increases entropy and expands the challenge–response space dramatically. Full article
(This article belongs to the Special Issue PUF-Based Authentication)
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4926 KiB  
Article
Analysis of Entropy in a Hardware-Embedded Delay PUF
by Wenjie Che, Venkata K. Kajuluri, Mitchell Martin, Fareena Saqib and Jim Plusquellic
Cryptography 2017, 1(1), 8; https://doi.org/10.3390/cryptography1010008 - 7 Jun 2017
Cited by 20 | Viewed by 11015
Abstract
The magnitude of the information content associated with a particular implementation of a Physical Unclonable Function (PUF) is critically important for security and trust in emerging Internet of Things (IoT) applications. Authentication, in particular, requires the PUF to produce a very large number [...] Read more.
The magnitude of the information content associated with a particular implementation of a Physical Unclonable Function (PUF) is critically important for security and trust in emerging Internet of Things (IoT) applications. Authentication, in particular, requires the PUF to produce a very large number of challenge-response-pairs (CRPs) and, of even greater importance, requires the PUF to be resistant to adversarial attacks that attempt to model and clone the PUF (model-building attacks). Entropy is critically important to the model-building resistance of the PUF. A variety of metrics have been proposed for reporting Entropy, each measuring the randomness of information embedded within PUF-generated bitstrings. In this paper, we report the Entropy, MinEntropy, conditional MinEntropy, Interchip hamming distance and National Institute of Standards and Technology (NIST) statistical test results using bitstrings generated by a Hardware-Embedded Delay PUF called HELP. The bitstrings are generated from data collected in hardware experiments on 500 copies of HELP implemented on a set of Xilinx Zynq 7020 SoC Field Programmable Gate Arrays (FPGAs) subjected to industrial-level temperature and voltage conditions. Special test cases are constructed which purposely create worst case correlations for bitstring generation. Our results show that the processes proposed within HELP to generate bitstrings add significantly to their Entropy, and show that classical re-use of PUF components, e.g., path delays, does not result in large Entropy losses commonly reported for other PUF architectures. Full article
(This article belongs to the Special Issue PUF-Based Authentication)
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