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How Deep Learning Helps Compromising USIM
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0003-2349-3920
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems, Electronic and embedded systems.ORCID iD: 0000-0001-7382-9408
2021 (English)In: Smart Card Research and Advanced Applications, CARDIS 2020 / [ed] Liardet, PY Mentens, N, Springer Nature , 2021, Vol. 12609, p. 135-150Conference paper, Published paper (Refereed)
Abstract [en]

It is known that secret keys can be extracted from some USIM cards using Correlation Power Analysis (CPA). In this paper, we demonstrate a more advanced attack on USIMs, based on deep learning. We show that a Convolutional Neural Network (CNN) trained on one USIM can recover the key from another USIM using at most 20 traces (four traces on average). Previous CPA attacks on USIM cards required high-quality oscilloscopes for power trace acquisition, an order of magnitude more traces from the victim card, and expert-level skills from the attacker. Now the attack can be mounted with a $1000 budget and basic skills in side-channel analysis.

Place, publisher, year, edition, pages
Springer Nature , 2021. Vol. 12609, p. 135-150
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 12609
Keywords [en]
USIM, MILENAGE, AES, Power analysis, Deep learning
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-306350DOI: 10.1007/978-3-030-68487-7_9ISI: 000723846600009Scopus ID: 2-s2.0-85101845297OAI: oai:DiVA.org:kth-306350DiVA, id: diva2:1620256
Conference
19th International Conference on Smart Card Research and Advanced Applications, CARDIS 2020 Virtual, Online18 November 2020 through 19 November 2020
Note

QC 20211215

Part of proceeding: ISBN 978-3-030-68487-7; 978-3-030-68486-0

Available from: 2021-12-15 Created: 2021-12-15 Last updated: 2022-06-25Bibliographically approved

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Brisfors, MartinForsmark, SebastianDubrova, Elena

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CiteExportLink to record
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