S-NET: A Confusion Based Countermeasure Against Power Attacks for SBOX

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Abstract

Side channel attacks are recognized as one of the most powerful attacks due to their ability to extract secret key information by analyzing the unintended leakage generated during operation. This makes them highly attractive for attackers. The current countermeasures focus on either randomizing the leakage by obfuscating the power consumption of all operations or blinding the leakage by maintaining a similar power consumption for all operations. Although these techniques help hiding the power-leakage correlation, they do not remove the correlation completely. This paper proposes a new countermeasure type, referred to as confusion, that aims to break the linear correlation between the leakage model and the power consumption and hence confuses attackers. It realizes this by replacing the traditional SBOX implementation with a neural network referred to as S-NET. As a case study, the security of Advanced Encryption Standard (AES) software implementations with both conventional SBOX and S-NET are evaluated. Based on our experimental results, S-NET leaks no information and is resilient against popular attacks such as differential and correlation power analysis.

Original languageEnglish
Title of host publicationEmbedded Computer Systems
Subtitle of host publicationArchitectures, Modeling, and Simulation - 20th International Conference, SAMOS 2020, Proceedings
EditorsAlex Orailoglu, Matthias Jung, Marc Reichenbach
PublisherSpringer
Pages295-307
Number of pages13
ISBN (Print)9783030609382
DOIs
Publication statusPublished - 2020
Event20th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2020 - Samos, Greece
Duration: 5 Jul 20209 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12471 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2020
CountryGreece
CitySamos
Period5/07/209/07/20

Keywords

  • Advanced Encryption Standard
  • Neural network
  • S-NET
  • SBOX
  • Side channel analysis

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