Higher Order Leakage Assessment and Neural Network-based Attack on CRYSTALS-Kyber

Buvana Ganesh; Mosabbah Ahmed; Alieeldin Mady

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Paper

Higher Order Leakage Assessment and Neural Network-based Attack on CRYSTALS-Kyber

Topics: AI-based Security and Privacy; Risk Assessment; Security Engineering

In Proceedings of the 21st International Conference on Security and Cryptography SECRYPT - Volume 1, 373-380, 2024 , Dijon, France

Authors: Buvana Ganesh ; Mosabbah Ahmed and Alieeldin Mady

Affiliation: Qualcomm Inc., Cork, Ireland

Keyword(s): Side Channel Attacks, CRYSTALS-Kyber, Leakage Assessment, Deep Learning, Higher Order Masking.

Abstract: To enable the secure deployment of CRYSTALS-Kyber as the National Institute of Standards and Technology (NIST) post-quantum cryptography (PQC) standard for key encapsulation mechanisms (KEM), several attacks have emerged for both the algorithm and its implementations. In this work, a thorough higher order test vector leakage assessment has been performed on open source implementations of CRYSTALS-Kyber. With the traces obtained using the ChipWhisperer framework, the leakage is determined and a template Side Channel Attacks (SCA) is performed with deep learning to successfully uncover the secret key from the first-order masked implementation of CRYSTALS-Kyber. Overall, this work performs a comprehensive leakage assessment and neural network-based SCAs on the masked implementation of CRYSTALS-Kyber.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Ganesh, B. ; Ahmed, M. and Mady, A. (2024). Higher Order Leakage Assessment and Neural Network-based Attack on CRYSTALS-Kyber. In Proceedings of the 21st International Conference on Security and Cryptography - SECRYPT; ISBN 978-989-758-709-2; ISSN 2184-7711, SciTePress, pages 373-380. DOI: 10.5220/0012715700003767

@conference{secrypt24,
author={Buvana Ganesh and Mosabbah Ahmed and Alieeldin Mady},
title={Higher Order Leakage Assessment and Neural Network-based Attack on CRYSTALS-Kyber},
booktitle={Proceedings of the 21st International Conference on Security and Cryptography - SECRYPT},
year={2024},
pages={373-380},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012715700003767},
isbn={978-989-758-709-2},
issn={2184-7711},
}

TY - CONF

JO - Proceedings of the 21st International Conference on Security and Cryptography - SECRYPT
TI - Higher Order Leakage Assessment and Neural Network-based Attack on CRYSTALS-Kyber
SN - 978-989-758-709-2
IS - 2184-7711
AU - Ganesh, B.
AU - Ahmed, M.
AU - Mady, A.
PY - 2024
SP - 373
EP - 380
DO - 10.5220/0012715700003767
PB - SciTePress