Focus is Key to Success

Focus is Key to Success: A Focal Loss Function for Deep Learning-Based Side-Channel Analysis

Kerkhof, Maikel (Student TU Delft)
Wu, L. (TU Delft Cyber Security)
Perin, G. (TU Delft Cyber Security)
Picek, S. (TU Delft Cyber Security; Radboud Universiteit Nijmegen)

Balasch, Josep (editor)
O’Flynn, Colin (editor)

2022

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.

Deep learning
Focal loss
Loss function
Side-channel analysis

http://resolver.tudelft.nl/uuid:ae6acb31-652c-4ae4-b64a-124f22f6acdb

https://doi.org/10.1007/978-3-030-99766-3_2

Springer

2022-10-03

9783030997656

Constructive Side-Channel Analysis and Secure Design - 13th International Workshop, COSADE 2022, Proceedings, 13211

13th International Workshop on Constructive Side-Channel Analysis and Secure Design, COSADE 2022, 2022-04-11 → 2022-04-12, Leuven, Belgium

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 0302-9743, 13211 LNCS

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-care Otherwise 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.

Institutional Repository

conference paper

© 2022 Maikel Kerkhof, L. Wu, G. Perin, S. Picek