IEICE TRANSACTIONS on Fundamentals
On the Signal-to-Noise Ratio for Boolean Functions
Summary :
The notion of the signal-to-noise ratio (SNR), proposed by Guilley, et al. in 2004, is a property that attempts to characterize the resilience of (n, m)-functions F=(f1,...,fm) (cryptographic S-boxes) against differential power analysis. But how to study the signal-to-noise ratio for a Boolean function still appears to be an important direction. In this paper, we give a tight upper and tight lower bounds on SNR for any (balanced) Boolean function. We also deduce some tight upper bounds on SNR for balanced Boolean function satisfying propagation criterion. Moreover, we obtain a SNR relationship between an n-variable Boolean function and two (n-1)-variable decomposition functions. Meanwhile, we give SNR(f⊞g) and SNR(f⊡g) for any balanced Boolean functions f, g. Finally, we give a lower bound on SNR(F), which determined by SNR(fi) (1≤i≤m), for (n, m)-function F=(f1,f2,…,fm).
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E103-A No.12 pp.1659-1665
- Publication Date
- 2020/12/01
- Publicized
- 2020/05/25
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2020EAL2037
- Type of Manuscript
- LETTER
- Category
- Cryptography and Information Security
Authors
Yu ZHOU
the Science and Technology on Communication Security Laboratory
Wei ZHAO
the Science and Technology on Communication Security Laboratory
Zhixiong CHEN
Putian University
Weiqiong WANG
Chang'an University
Xiaoni DU
Northwest Normal University
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Yu ZHOU, Wei ZHAO, Zhixiong CHEN, Weiqiong WANG, Xiaoni DU, "On the Signal-to-Noise Ratio for Boolean Functions" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 12, pp. 1659-1665, December 2020, doi: 10.1587/transfun.2020EAL2037.
Abstract: The notion of the signal-to-noise ratio (SNR), proposed by Guilley, et al. in 2004, is a property that attempts to characterize the resilience of (n, m)-functions F=(f1,...,fm) (cryptographic S-boxes) against differential power analysis. But how to study the signal-to-noise ratio for a Boolean function still appears to be an important direction. In this paper, we give a tight upper and tight lower bounds on SNR for any (balanced) Boolean function. We also deduce some tight upper bounds on SNR for balanced Boolean function satisfying propagation criterion. Moreover, we obtain a SNR relationship between an n-variable Boolean function and two (n-1)-variable decomposition functions. Meanwhile, we give SNR(f⊞g) and SNR(f⊡g) for any balanced Boolean functions f, g. Finally, we give a lower bound on SNR(F), which determined by SNR(fi) (1≤i≤m), for (n, m)-function F=(f1,f2,…,fm).
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2020EAL2037/_p
Copy
@ARTICLE{e103-a_12_1659,
author={Yu ZHOU, Wei ZHAO, Zhixiong CHEN, Weiqiong WANG, Xiaoni DU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={On the Signal-to-Noise Ratio for Boolean Functions},
year={2020},
volume={E103-A},
number={12},
pages={1659-1665},
abstract={The notion of the signal-to-noise ratio (SNR), proposed by Guilley, et al. in 2004, is a property that attempts to characterize the resilience of (n, m)-functions F=(f1,...,fm) (cryptographic S-boxes) against differential power analysis. But how to study the signal-to-noise ratio for a Boolean function still appears to be an important direction. In this paper, we give a tight upper and tight lower bounds on SNR for any (balanced) Boolean function. We also deduce some tight upper bounds on SNR for balanced Boolean function satisfying propagation criterion. Moreover, we obtain a SNR relationship between an n-variable Boolean function and two (n-1)-variable decomposition functions. Meanwhile, we give SNR(f⊞g) and SNR(f⊡g) for any balanced Boolean functions f, g. Finally, we give a lower bound on SNR(F), which determined by SNR(fi) (1≤i≤m), for (n, m)-function F=(f1,f2,…,fm).},
keywords={},
doi={10.1587/transfun.2020EAL2037},
ISSN={1745-1337},
month={December},}
Copy
TY - JOUR
TI - On the Signal-to-Noise Ratio for Boolean Functions
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1659
EP - 1665
AU - Yu ZHOU
AU - Wei ZHAO
AU - Zhixiong CHEN
AU - Weiqiong WANG
AU - Xiaoni DU
PY - 2020
DO - 10.1587/transfun.2020EAL2037
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2020
AB - The notion of the signal-to-noise ratio (SNR), proposed by Guilley, et al. in 2004, is a property that attempts to characterize the resilience of (n, m)-functions F=(f1,...,fm) (cryptographic S-boxes) against differential power analysis. But how to study the signal-to-noise ratio for a Boolean function still appears to be an important direction. In this paper, we give a tight upper and tight lower bounds on SNR for any (balanced) Boolean function. We also deduce some tight upper bounds on SNR for balanced Boolean function satisfying propagation criterion. Moreover, we obtain a SNR relationship between an n-variable Boolean function and two (n-1)-variable decomposition functions. Meanwhile, we give SNR(f⊞g) and SNR(f⊡g) for any balanced Boolean functions f, g. Finally, we give a lower bound on SNR(F), which determined by SNR(fi) (1≤i≤m), for (n, m)-function F=(f1,f2,…,fm).
ER -
English
