Physical unclonable function

PUFs act as digital uniquely identifying fingerprints[1]

A physical unclonable function (sometimes also called physically-unclonable function, which refers to a weaker security metric than a physical unclonable function [citation needed]), or PUF, is a physical object whose operation cannot be reproduced ("cloned") in physical way (by making another system using the same technology), that for a given input and conditions (challenge), provides a physically defined "digital fingerprint" output (response). that serves as a unique identifier, most often for a semiconductor device such as a microprocessor. PUFs are often based on unique physical variations occurring naturally during semiconductor manufacturing.[2] A PUF is a physical entity embodied in a physical structure. PUFs are implemented in integrated circuits, including FPGAs,[3] and can be used in applications with high-security requirements, more specifically cryptography, Internet of Things (IOT) devices [4] and privacy protection.[5]

  1. ^ Maes, Roel (2013), "Physically Unclonable Functions: Properties", Physically Unclonable Functions, Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 49–80, doi:10.1007/978-3-642-41395-7_3, ISBN 978-3-642-41394-0, retrieved 2023-04-07
  2. ^ Kamal, Kamal Y.; Muresan, Radu (2019). "Mixed-Signal Physically Unclonable Function With CMOS Capacitive Cells". IEEE Access. 7: 130977–130998. Bibcode:2019IEEEA...7m0977K. doi:10.1109/ACCESS.2019.2938729. hdl:10214/17525. ISSN 2169-3536. S2CID 202766809.
  3. ^ Nozaki, Yusuke; Yoshikawa, Masaya (May 2019). "Countermeasure of Lightweight Physical Unclonable Function Against Side-Channel Attack". 2019 Cybersecurity and Cyberforensics Conference (CCC). Melbourne, Australia: IEEE. pp. 30–34. doi:10.1109/CCC.2019.00-13. ISBN 978-1-7281-2600-5. S2CID 203655491.
  4. ^ Josiah, J. G. (2020). The CCAP: A New Physical Unclonable Function (PUF) for Protecting Internet of Things (IoT) and Other FPGA-based Embedded Systems. ProQuest (Ph.D). ProQuest 2406630562.
  5. ^ Lipps, Christoph; Mallikarjun, Sachinkumar Bavikatti; Strufe, Matthias; Heinz, Christopher; Grimm, Christoph; Schotten, Hans Dieter (June 2020). "Keep Private Networks Private: Secure Channel-PUFs, and Physical Layer Security by Linear Regression Enhanced Channel Profiles". 2020 3rd International Conference on Data Intelligence and Security (ICDIS). IEEE. pp. 93–100. doi:10.1109/icdis50059.2020.00019. ISBN 978-1-7281-9379-3. S2CID 231683963.