Cryptology ePrint Archive: Report 2020/1534

Improved Differential Fault Attack on LEA by Algebraic Representation of Modular Addition

SeongHyuck Lim and JongHyeok Lee and Dong-Guk Han

Abstract: Recently, as the number of IoT (Internet of Things) devices has increased, the use of lightweight cryptographic algorithms that are suitable for environments with scarce resources has also increased. Consequently, the safety of such cryptographic algorithms is becoming increasingly important. Among them, side-channel analysis methods are very realistic threats. In this paper, we propose a novel differential fault attack method on the Lightweight Encryption Algorithm (LEA) cipher which became the ISO/IEC international standard lightweight cryptographic algorithm in 2019. Previously proposed differential fault attack methods on the LEA used the Single Bit Flip model, making it difficult to apply to real devices. The proposed attack method uses a more realistic attacker assumption, the Random Word Error model. We demonstrate that the proposed attack method can be implemented on real devices using an electromagnetic fault injection setup. Our attack method has the weakest attacker assumption among attack methods proposed to date. In addition, the number of required fault-injected ciphertexts and the number of key candidates for which exhaustive search is performed are the least among all existing methods. Therefore, when implementing the LEA cipher on IoT deivces, designers must apply appropriate countermeasures against fault injection attacks.

Category / Keywords: secret-key cryptography / Side-Channel Analysis, Differential Fault Attack, Fault Injection Attack, Lightweight Cryptography, ARX-based Cryptography, LEA

Original Publication (in the same form): IEEE Access
DOI:
10.1109/ACCESS.2020.3039805.

Date: received 8 Dec 2020

Contact author: seonghyeck16 at kookmin ac kr,n_seeu@kookmin ac kr,christa@kookmin ac kr

Available format(s): PDF | BibTeX Citation

Version: 20201213:163544 (All versions of this report)

Short URL: ia.cr/2020/1534


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