Paper 2019/1071
DLSCA: a Tool for Deep Learning Side Channel Analysis
Martin Brisfors and Sebastian Forsmark
Abstract
Abstract - Research on Side Channel Analysis (SCA) is very active and progressing at a fast pace. The idea of using Machine Learning (ML), and more recently Deep Learning(DL), to help SCA data is explored extensively. One issue facing security researchers interested in contributing to this cause is the difficulties getting started. While replicating previous works with open source code is not difficult, taking the next steps from there can be daunting. The presented open-source DLSCA tool is created to aid with research on DL-based SCA and to help newcomers to DL to get started. It is hoped to contribute to investigating the strengths and limitations of ML-based SCA. Keywords - Machine Learning, Side Channel Attack, Software Tool
Metadata
- Available format(s)
- Category
- Secret-key cryptography
- Publication info
- Preprint. MINOR revision.
- Keywords
- Machine LearningSide Channel AttackSoftware Tool
- Contact author(s)
-
brisfors @ kth se
sforsm @ kth se - History
- 2019-09-23: revised
- 2019-09-23: received
- See all versions
- Short URL
- https://ia.cr/2019/1071
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2019/1071, author = {Martin Brisfors and Sebastian Forsmark}, title = {{DLSCA}: a Tool for Deep Learning Side Channel Analysis}, howpublished = {Cryptology {ePrint} Archive, Paper 2019/1071}, year = {2019}, url = {https://eprint.iacr.org/2019/1071} }