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MAG-PUF: Magnetic Physical Unclonable Functions for Device Authentication in the IoT

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Security and Privacy in Communication Networks (SecureComm 2022)

Abstract

Authenticating Internet of Things (IoT) devices is still a challenge, especially in deployments involving low-cost constrained nodes. The cited class of IoT devices hardly support dynamic re-keying solutions, hence being vulnerable to several attacks. To provide a viable general-purpose solution, in this paper we propose MAG-PUF, a novel lightweight authentication scheme based on the usage of unintentional magnetic emissions generated by IoT devices as Physical Unclonable Functions (PUFs). Specifically, through MAG-PUF, we collect unintentional magnetic emissions produced by the IoT devices at run-time while executing pre-defined reference functions, and we verify the match of such emissions with the profiles collected at enrolment time, providing device authentication. MAG-PUF enjoys unique flexibility, allowing the selection of an unlimited number and types of reference functions. We extensively assessed the performance of MAG-PUF through experiments on 25 Arduino devices and a set of exemplary reference functions. We obtained an authentication accuracy above 99%, hence proving the feasibility of using code-driven magnetic emissions as a lightweight, efficient, and robust PUF for IoT devices.

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Acknowledgements

This publication was partially supported by award GSRA6-1-0528-19046, from the QNRF-Qatar National Research Fund, a member of Qatar Foundation. The information and views set out in this publication are those of the authors and do not necessarily reflect the official opinion of the QNRF. This publication was also partially supported by the INTERSECT project, Grant No. NWA.1162.18.301, funded by Netherlands Organization for Scientific Research (NWO) and the NATO Science for Peace and Security Programme - MYP G5828 project “SeaSec: DronNets for Maritime Border and Port Security”.

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Authors and Affiliations

  1. College of Science and Engineering (CSE), Information and Computing Technology (ICT) Division, Hamad Bin Khalifa University (HBKU), Doha, Qatar

    Omar Adel Ibrahim & Roberto Di Pietro

  2. Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands

    Savio Sciancalepore

  3. Eindhoven Artificial Intelligence Systems Institute (EAISI), Eindhoven, The Netherlands

    Savio Sciancalepore

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  1. Omar Adel Ibrahim
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  2. Savio Sciancalepore
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Correspondence to Omar Adel Ibrahim .

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Editors and Affiliations

  1. University of Kansas, Lawrence, KS, USA

    Fengjun Li

  2. Delft University of Technology, Delft, The Netherlands

    Kaitai Liang

  3. The Ohio State University, Columbus, OH, USA

    Zhiqiang Lin

  4. Norwegian University of Science and Tech, Gjøvik, Norway

    Sokratis K. Katsikas

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Ibrahim, O.A., Sciancalepore, S., Di Pietro, R. (2023). MAG-PUF: Magnetic Physical Unclonable Functions for Device Authentication in the IoT. In: Li, F., Liang, K., Lin, Z., Katsikas, S.K. (eds) Security and Privacy in Communication Networks. SecureComm 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 462. Springer, Cham. https://doi.org/10.1007/978-3-031-25538-0_8

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