International Association for Cryptologic Research

International Association
for Cryptologic Research


Paper: Deep Learning to Evaluate Secure RSA Implementations

Mathieu Carbone , SERMA Safety and Security
Vincent Conin , SERMA Safety and Security
Marie-Angela Cornélie , CEA LETI
François Dassance , Thales ITSEF
Guillaume Dufresne , Thales ITSEF, France
Cécile Dumas , CEA LETI
Emmanuel Prouff , ANSSI
Alexandre Venelli , Thales ITSEF
DOI: 10.13154/tches.v2019.i2.132-161
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Presentation: Slides
Abstract: This paper presents the results of several successful profiled side-channel attacks against a secure implementation of the RSA algorithm. The implementation was running on a ARM Core SC 100 completed with a certified EAL4+ arithmetic co-processor. The analyses have been conducted by three experts’ teams, each working on a specific attack path and exploiting information extracted either from the electromagnetic emanation or from the power consumption. A particular attention is paid to the description of all the steps that are usually followed during a security evaluation by a laboratory, including the acquisitions and the observations preprocessing which are practical issues usually put aside in the literature. Remarkably, the profiling portability issue is also taken into account and different device samples are involved for the profiling and testing phases. Among other aspects, this paper shows the high potential of deep learning attacks against secure implementations of RSA and raises the need for dedicated countermeasures.
Video from TCHES 2019
  title={Deep Learning to Evaluate Secure RSA Implementations},
  journal={IACR Transactions on Cryptographic Hardware and Embedded Systems},
  publisher={Ruhr-Universität Bochum},
  volume={2019, Issue 2},
  author={Mathieu Carbone and Vincent Conin and Marie-Angela Cornélie and François Dassance and Guillaume Dufresne and Cécile Dumas and Emmanuel Prouff and Alexandre Venelli},