A side-channel attack on a masked and shuffled software implementation of Saber
Ngo, Kalle ; Dubrova, Elena and Johansson, Thomas LU
(2023)
In Journal of Cryptographic Engineering
13(4).
p.443-460
- Abstract
In this paper, we show that a software implementation of IND-CCA-secure Saber key encapsulation mechanism protected by first-order masking and shuffling can be broken by deep learning-based power analysis. Using an ensemble of deep neural networks trained at the profiling stage, we can recover the session key and the secret key from 257 × N and 24 × 257 × N traces, respectively, where N is the number of repetitions of the same measurement. The value of N depends on the implementation of the algorithm, the type of device under attack, environmental factors, acquisition noise, etc.; in our experiments N= 10 is sufficient for a successful attack. The neural networks are trained on a combination of 80% of traces from the profiling device... (More)
In this paper, we show that a software implementation of IND-CCA-secure Saber key encapsulation mechanism protected by first-order masking and shuffling can be broken by deep learning-based power analysis. Using an ensemble of deep neural networks trained at the profiling stage, we can recover the session key and the secret key from 257 × N and 24 × 257 × N traces, respectively, where N is the number of repetitions of the same measurement. The value of N depends on the implementation of the algorithm, the type of device under attack, environmental factors, acquisition noise, etc.; in our experiments N= 10 is sufficient for a successful attack. The neural networks are trained on a combination of 80% of traces from the profiling device with a known shuffling order and 20% of traces from the device under attack captured for all-0 and all-1 messages. “Spicing” the training set with traces from the device under attack helps us minimize the negative effect of inter-device variability.
(Less)
- author
- Ngo, Kalle
; Dubrova, Elena
and Johansson, Thomas
LU
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- LWE/LWR-based KEM, Post-quantum cryptography, Power analysis, Public-key cryptography, Saber KEM, Side-channel attack
- in
- Journal of Cryptographic Engineering
- volume
- 13
- issue
- 4
- pages
- 443 - 460
- publisher
- Springer Science and Business Media B.V.
- external identifiers
-
- scopus:85153507371
- ISSN
- 2190-8508
- DOI
- 10.1007/s13389-023-00315-3
- language
- English
- LU publication?
- yes
- id
- 83594629-acf2-424a-9161-122233e4fb4a
- date added to LUP
- 2023-07-14 11:12:59
- date last changed
- 2025-04-04 14:28:05
@article{83594629-acf2-424a-9161-122233e4fb4a,
abstract = {{<p>In this paper, we show that a software implementation of IND-CCA-secure Saber key encapsulation mechanism protected by first-order masking and shuffling can be broken by deep learning-based power analysis. Using an ensemble of deep neural networks trained at the profiling stage, we can recover the session key and the secret key from 257 × N and 24 × 257 × N traces, respectively, where N is the number of repetitions of the same measurement. The value of N depends on the implementation of the algorithm, the type of device under attack, environmental factors, acquisition noise, etc.; in our experiments N= 10 is sufficient for a successful attack. The neural networks are trained on a combination of 80% of traces from the profiling device with a known shuffling order and 20% of traces from the device under attack captured for all-0 and all-1 messages. “Spicing” the training set with traces from the device under attack helps us minimize the negative effect of inter-device variability.</p>}},
author = {{Ngo, Kalle and Dubrova, Elena and Johansson, Thomas}},
issn = {{2190-8508}},
keywords = {{LWE/LWR-based KEM; Post-quantum cryptography; Power analysis; Public-key cryptography; Saber KEM; Side-channel attack}},
language = {{eng}},
number = {{4}},
pages = {{443--460}},
publisher = {{Springer Science and Business Media B.V.}},
series = {{Journal of Cryptographic Engineering}},
title = {{A side-channel attack on a masked and shuffled software implementation of Saber}},
url = {{http://dx.doi.org/10.1007/s13389-023-00315-3}},
doi = {{10.1007/s13389-023-00315-3}},
volume = {{13}},
year = {{2023}},
}