Refinement and Empirical Side-Channel Analysis of Inner Product Masking with Robust Error Detection

Anton Maidl, Mael Gay, Osnat Keren, Ilia Polian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Side-channel attacks represent a significant and persistent threat to hardware security. One effective strategy for safeguarding hardware components against these attacks involves the implementation of masking schemes. Among these schemes, Inner Product Masking (IPM) has received considerable attention and analysis in prior research. Inner Product Masking with Error Detection aims to extend the security provided by IPM to Fault-Injection attacks. This can be achieved by incorporating (linear) repetition code for fault detection (IPM-FD) or by integrating a non-linear robust error detection into the scheme (IPM-RED). IPM-RED can detect (with non-zero probability) every fault regardless the number of bits it flips. However, this robustness comes with a cost, a non-linear function may leak via the physical channels more information than a linear one. This paper shows that information leakage from IPM-RED is marginal. An improved IPM-RED masking scheme is also presented, and an empirical side-channel leakage analysis of the protected Advanced Encryption Standard (AES) design utilizing the Test Vector Leakage Assessment (TVLA).

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE 30th International Symposium on On-line Testing and Robust System Design, IOLTS 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350370553
DOIs
StatePublished - 2024
Event30th IEEE International Symposium on On-line Testing and Robust System Design, IOLTS 2024 - Rennes, France
Duration: 3 Jul 20245 Jul 2024

Publication series

NameProceedings - 2024 IEEE 30th International Symposium on On-line Testing and Robust System Design, IOLTS 2024

Conference

Conference30th IEEE International Symposium on On-line Testing and Robust System Design, IOLTS 2024
Country/TerritoryFrance
CityRennes
Period3/07/245/07/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Fingerprint

Dive into the research topics of 'Refinement and Empirical Side-Channel Analysis of Inner Product Masking with Robust Error Detection'. Together they form a unique fingerprint.

Cite this