Kilroy Was Here: The First Step Towards Explainability of Neural Networks in Profiled Side-Channel Analysis

Daan Valk, Stjepan Picek*, Shivam Bhasin

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

While several works have explored the application of deep learning for efficient profiled side-channel analysis, explainability, or, in other words, what neural networks learn remains a rather untouched topic. As a first step, this paper explores the Singular Vector Canonical Correlation Analysis (SVCCA) tool to interpret what neural networks learn while training on different side-channel datasets, by concentrating on deep layers of the network. Information from SVCCA can help, to an extent, with several practical problems in a profiled side-channel analysis like portability issue and criteria to choose a number of layers/neurons to fight portability, provide insight on the correct size of training dataset and detect deceptive conditions like over-specialization of networks.

Original languageEnglish
Title of host publicationConstructive Side-Channel Analysis and Secure Design - 11th International Workshop, COSADE 2020, Revised Selected Papers
EditorsGuido Marco Bertoni, Francesco Regazzoni
PublisherSpringer
Pages175-199
Number of pages25
Volume12244
ISBN (Print)9783030687724
DOIs
Publication statusPublished - 2021
Event11th International Workshop on Constructive Side-Channel Analysis and Secure Design, COSADE 2020 - Lugano, Switzerland
Duration: 1 Apr 20203 Apr 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12244 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Workshop on Constructive Side-Channel Analysis and Secure Design, COSADE 2020
Country/TerritorySwitzerland
CityLugano
Period1/04/203/04/20

Keywords

  • Deep learning
  • Neural networks
  • Representation learning
  • Side-channel analysis

Fingerprint

Dive into the research topics of 'Kilroy Was Here: The First Step Towards Explainability of Neural Networks in Profiled Side-Channel Analysis'. Together they form a unique fingerprint.

Cite this