It’s a Kind of Magic: A Novel Conditional GAN Framework for Efficient Profiling Side-Channel Analysis

Sengim Karayalçın*, Marina Krček, Lichao Wu, Stjepan Picek, Guilherme Perin

*Corresponding author for this work

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

Abstract

Profiling side-channel analysis (SCA) is widely used to evaluate the security of cryptographic implementations under worst-case attack scenarios. This method assumes a strong adversary with a fully controlled device clone, known as a profiling device, with full access to the internal state of the target algorithm, including the mask shares. However, acquiring such a profiling device in the real world is challenging, as secure products enforce strong life cycle protection, particularly on devices that allow the user partial (e.g., debug mode) or full (e.g., test mode) control. This enforcement restricts access to profiling devices, significantly reducing the effectiveness of profiling SCA. To address this limitation, this paper introduces a novel framework that allows an attacker to create and learn from their own white-box reference design without needing privileged access on the profiling device. Specifically, the attacker first implements the target algorithm on a different type of device with full control. Since this device is a white box to the attacker, they can access all internal states and mask shares. A novel conditional generative adversarial network (CGAN) framework is then introduced to mimic the feature extraction procedure from the reference device and transfer this experience to extract high-order leakages from the target device. These extracted features then serve as inputs for profiled SCA. Experiments show that our approach significantly enhances the efficacy of black-box profiling SCA, matching or potentially exceeding the results of worst-case security evaluations. Compared with conventional profiling SCA, which has strict requirements on the profiling device, our framework relaxes this threat model and, thus, can be better adapted to real-world attacks.

Original languageEnglish
Title of host publicationAdvances in Cryptology – ASIACRYPT 2024 - 30th International Conference on the Theory and Application of Cryptology and Information Security, Proceedings
EditorsKai-Min Chung, Yu Sasaki
PublisherSpringer
Pages99-131
Number of pages33
ISBN (Print)9789819609437
DOIs
Publication statusPublished - 2025
Event30th Annual International Conference on the Theory and Application of Cryptology and Information Security, ASIACRYPT 2024 - Kolkata, India
Duration: 9 Dec 202413 Dec 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15491 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference30th Annual International Conference on the Theory and Application of Cryptology and Information Security, ASIACRYPT 2024
Country/TerritoryIndia
CityKolkata
Period9/12/2413/12/24

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-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

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