Challenges in deep learning-based profiled side-channel analysis

Stjepan Picek*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

In recent years, profiled side-channel attacks based on machine learning proved to be very successful in breaking cryptographic implementations in various settings. Still, despite successful attacks even in the presence of countermeasures, there are many open questions. A large part of the research concentrates on improving the performance of attacks while little is done to understand them and even more importantly, use that knowledge in the design of more secure implementations. In this paper, we start by briefly recollecting on the state-of-the-art in machine learning-based side-channel analysis. Afterward, we discuss several challenges we believe will play an important role in future research.

Original languageEnglish
Title of host publicationSecurity, Privacy, and Applied Cryptography Engineering - 9th International Conference, SPACE 2019, Proceedings
EditorsShivam Bhasin, Avi Mendelson, Mridul Nandi
PublisherSpringer
Pages9-12
Number of pages4
Volume11947
ISBN (Print)9783030358686
DOIs
Publication statusPublished - 1 Jan 2019
Event9th International Conference on Security, Privacy, and Applied Cryptography Engineering, SPACE 2019 - Gandhinagar, India
Duration: 3 Dec 20197 Dec 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11947 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Security, Privacy, and Applied Cryptography Engineering, SPACE 2019
CountryIndia
CityGandhinagar
Period3/12/197/12/19

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