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CBDC-PUF: A Novel Physical Unclonable Function Design Framework Utilizing Configurable Butterfly Delay Chain Against Modeling Attack

Published: 08 September 2023 Publication History

Abstract

Physical unclonable function (PUF) is a promising security-based primitive, which provides an extremely large number of responses for key generation and authentication applications. Various PUFs have been developed as central building blocks in cryptographic protocols and security architectures, however, the existing PUFs and their improvements are still vulnerable to modeling attacks (MA) with refined machine learning algorithms. In this article, a configurable butterfly delay chain-based PUF design framework is proposed to meet the requirements of randomness, reliability, uniqueness, and MA-resistance metrics. A configurable butterfly delay chain is introduced to create multiple pairs of symmetric paths and a strong PUF relying on the intrinsic delay fluctuations of two identical paths is built. Furthermore, a secure hash function is used to insert non-linearities into the PUF, and a BCH-based error correction algorithm is utilized to recover the actual responses under noisy environments. The proposed PUF is implemented on Xilinx FPGAs and three machine learning algorithms are used to evaluate the resistance against MA. Experimental results show that the randomness, reliability, and uniqueness of the proposed PUF are close to the ideal value (49.6%, 99.9%, and 49.9%, respectively), and the prediction accuracy reaches 50% that indicating a desirable resilient to MA.

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  1. CBDC-PUF: A Novel Physical Unclonable Function Design Framework Utilizing Configurable Butterfly Delay Chain Against Modeling Attack

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    Published In

    cover image ACM Transactions on Design Automation of Electronic Systems
    ACM Transactions on Design Automation of Electronic Systems  Volume 28, Issue 5
    September 2023
    475 pages
    ISSN:1084-4309
    EISSN:1557-7309
    DOI:10.1145/3623508
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    Association for Computing Machinery

    New York, NY, United States

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    Publication History

    Published: 08 September 2023
    Online AM: 21 March 2023
    Accepted: 04 March 2023
    Revised: 24 January 2023
    Received: 15 July 2022
    Published in TODAES Volume 28, Issue 5

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    Author Tags

    1. Physical unclonable function
    2. modeling attack
    3. machine learning algorithm
    4. cryptographic hash function

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    • (2024)Central bank digital currencies: a comprehensive systematic literature review on worldwide research emergence and methods usedAmerican Journal of Business10.1108/AJB-12-2023-021039:3(137-157)Online publication date: 28-May-2024
    • (2024)Adaptive PUF design to authenticate and evaluate heterogeneous IPs in edge computingThe Journal of Supercomputing10.1007/s11227-024-06371-880:16(24689-24717)Online publication date: 1-Nov-2024
    • (2023)FPGA-Based PUF Designs: A Comprehensive Review and Comparative AnalysisCryptography10.3390/cryptography70400557:4(55)Online publication date: 1-Nov-2023

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