Cryptology ePrint Archive: Report 2019/545

Transform-and-Encode: A Countermeasure Framework for Statistical Ineffective Fault Attacks on Block Ciphers

Sayandeep Saha and Dirmanto Jap and Debapriya Basu Roy and Avik Chakraborti and Shivam Bhasin and Debdeep Mukhopadhyay

Abstract: Right from its introduction by Boneh et al., fault attacks (FA) have been established to be one of the most practical threats to both public key and symmetric key based cryptosystems. Statistical Ineffective Fault Analysis (SIFA) is a recently proposed class of fault attacks introduced at CHES 2018. The fascinating feature of this attack is that it exploits the correct ciphertexts obtained during a fault injection campaign, instead of the faulty ciphertexts. The SIFA has been shown to bypass almost all of the existing fault attack countermeasures even when they are combined with provably secure masking schemes for side-channel resistance. The goal of this work is to propose a countermeasure for SIFA. It has been observed that a randomized domain transformation of the intermediate computation combined with bit-level error correction can throttle SIFA. The randomized domain transformation can be achieved by standard masking schemes. In fact, we prove that if biased faults are injected at the state register of a block cipher at a target round, then masking is sufficient to protect against SIFA, until all the shares for a specific bit are corrupted. However, masking alone cannot prevent SIFA if the faults are injected at certain specific locations inside the S-Boxes. To address this issue, we incorporate a bit-level error-correction mechanism. The strongest advantage of the proposed countermeasure, called AntiSIFA, is that it provides provable and quantifiable security guarantees. Proof-of-concept evaluations were performed on software implementations of the block cipher PRESENT, which correlates with the theoretical results.

Category / Keywords: implementation / Fault Attack and Block Cipher and Masking

Date: received 22 May 2019, withdrawn 6 Nov 2019

Contact author: sayandeep iitkgp at gmail com

Available format(s): (-- withdrawn --)

Version: 20191106:140755 (All versions of this report)

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