Abstract
The deep learning-based side-channel analysis represents one of the most powerful side-channel attack approaches. Thanks to its capability in dealing with raw features and countermeasures, it becomes the de facto standard approach for the SCA community. The recent works significantly improved the deep learning-based attacks from various perspectives, like hyperparameter tuning, design guidelines, or custom neural network architecture elements. Still, insufficient attention has been given to the core of the learning process - the loss function. This paper analyzes the limitations of the existing loss functions and then proposes a novel side-channel analysis-optimized loss function: Focal Loss Ratio (FLR), to cope with the identified drawbacks observed in other loss functions. To validate our design, we 1) conduct a thorough experimental study considering various scenarios (datasets, leakage models, neural network architectures) and 2) compare with other loss functions used in the deep learning-based side-channel analysis (both “traditional” ones and those designed for side-channel analysis). Our results show that FLR loss outperforms other loss functions in various conditions while not having computational overhead like some recent loss function proposals.
Original language | English |
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Title of host publication | Constructive Side-Channel Analysis and Secure Design - 13th International Workshop, COSADE 2022, Proceedings |
Editors | Josep Balasch, Colin O’Flynn |
Publisher | Springer |
Pages | 29-48 |
Number of pages | 20 |
Volume | 13211 |
ISBN (Print) | 9783030997656 |
DOIs | |
Publication status | Published - 2022 |
Event | 13th International Workshop on Constructive Side-Channel Analysis and Secure Design, COSADE 2022 - Leuven, Belgium Duration: 11 Apr 2022 → 12 Apr 2022 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13211 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 13th International Workshop on Constructive Side-Channel Analysis and Secure Design, COSADE 2022 |
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Country/Territory | Belgium |
City | Leuven |
Period | 11/04/22 → 12/04/22 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- Deep learning
- Focal loss
- Loss function
- Side-channel analysis