Paper 2019/515
A Countermeasure Against Statistical Ineffective Fault Analysis
Abstract
When considering practical attacks against cryptographic implementations, Fault Injection Attacks (FIA) pose a powerful tool that can recover the secret key within few encryptions. Over the past few decades they have become a well-studied topic both by academic an industry practitioners. Current state-of-the-art countermeasures against Fault Injection Attacks (FIA) provide good protection against analysis methods that require the differences in the correct and faulty ciphertext to derive the secret information, such as Differential Fault Analysis (DFA) or collision fault analysis. However, recent progress in Ineffective Fault Analysis (IFA) and Statistical IFA (SIFA) constitutes a real threat against cryptographic implementations. Such methods cannot be thwarted by standard FIA countermeasures that focus on detecting the change in the intermediate data. In this paper, we present a novel method based on error correcting codes that protects implementations against SIFA. We design a set of universal error-correcting gates that can be used for block cipher implementations. We analyze a hardware implementation of protected GIFT-64 and show that our method provides 100% protection against SIFA.
Metadata
- Available format(s)
-
PDF
- Category
- Implementation
- Publication info
- Published elsewhere. IEEE TCAS2
- DOI
- 10.1109/TCSII.2020.2989184
- Keywords
- fault injection attacks ineffective fault analysis countermeasures error-correcting codes SIFA
- Contact author(s)
- jbreier @ jbreier com
- History
- 2022-09-13: last of 4 revisions
- 2019-05-20: received
- See all versions
- Short URL
- https://ia.cr/2019/515
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2019/515,
author = {Jakub Breier and Mustafa Khairallah and Xiaolu Hou and Yang Liu},
title = {A Countermeasure Against Statistical Ineffective Fault Analysis},
howpublished = {Cryptology {ePrint} Archive, Paper 2019/515},
year = {2019},
doi = {10.1109/TCSII.2020.2989184},
url = {https://eprint.iacr.org/2019/515}
}
