Improving Single-Trace Attacks on the Number-Theoretic Transform for Cortex-M4 - Université Grenoble Alpes
Communication Dans Un Congrès Année : 2023

Improving Single-Trace Attacks on the Number-Theoretic Transform for Cortex-M4

Guilhèm Assael
  • Fonction : Auteur
  • PersonId : 1287468
Philippe Elbaz-Vincent
  • Fonction : Auteur
  • PersonId : 1287469
Guillaume Reymond
  • Fonction : Auteur
  • PersonId : 1287470

Résumé

The Number-Theoretic Transform (NTT) is a key feature for the efficiency of numerous lattice-based cryptographic schemes. The arithmetic structure of that operation makes it an important target for soft-analytical side-channel attacks, that are powerful single-trace side-channel attacks exploiting known arithmetic structure to improve noise tolerance. Among others, Pessl et al. used the belief-propagation technique to attack a software implementation of the Kyber key encapsulation mechanism for Arm Cortex-M4 microcontrollers. However, that implementation has since been thoroughly optimized, in particular through the use of an improved version of Plantard modular arithmetic. In this paper, we describe how we successfully attack the latest available version of this implementation. We show that precise knowledge of the implementation at hand allows for better performance of the belief-propagation technique. By modeling each individual arithmetic operation performed by the microcontroller, we are able to recover the secret values processed during the NTT, even with very noisy side-channel leakage. We also study some strategies for the attacker to either maximize the success rate, or minimize the runtime of the attack.
Fichier principal
Vignette du fichier
HOST2023 Single-trace attack on NTT with copyright.pdf (406.44 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04218166 , version 1 (28-09-2023)

Identifiants

Citer

Guilhèm Assael, Philippe Elbaz-Vincent, Guillaume Reymond. Improving Single-Trace Attacks on the Number-Theoretic Transform for Cortex-M4. 2023 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), May 2023, San Jose, United States. pp.111-121, ⟨10.1109/HOST55118.2023.10133270⟩. ⟨hal-04218166⟩
18 Consultations
54 Téléchargements

Altmetric

Partager

More