Welcome to the resource topic for 2023/1252
Title:
Towards Private Deep Learning-based Side-Channel Analysis using Homomorphic Encryption
Authors: Fabian Schmid, Shibam Mukherjee, Stjepan Picek, Marc Stöttinger, Fabrizio De Santis, Christian Rechberger
Abstract:Side-channel analysis certification is a process designed to certify the resilience of cryptographic hardware and software implementations against side-channel attacks.
In certain cases, third-party evaluations by external companies or departments are necessary due to limited budget, time, or even expertise with the penalty of a significant exchange of sensitive information during the evaluation process.
In this work, we investigate the potential of Homomorphic Encryption (HE) in performing side-channel analysis on HE-encrypted measurements. With HE applied to side-channel analysis (SCA), a third party can perform SCA on encrypted measurement data and provide the outcome of the analysis without gaining insights about the actual cryptographic implementation under test. To this end, we evaluate its feasibility by analyzing the impact of AI-based side-channel analysis using HE (private SCA) on accuracy and execution time and compare the results with an ordinary AI-based side-channel analysis (plain SCA).
Our work suggests that both unprotected and protected cryptographic implementations can be successfully attacked already today with standard server equipment and modern HE protocols/libraries, while the traces are HE-encrypted.
ePrint: https://eprint.iacr.org/2023/1252
See all topics related to this paper.
Feel free to post resources that are related to this paper below.
Example resources include: implementations, explanation materials, talks, slides, links to previous discussions on other websites.
For more information, see the rules for Resource Topics .