AutoEncodersDLSCA
Code underlying the publication: Autoencoder-enabled model portability for reducing hyperparameter tuning efforts in side-channel analysis
Description
Link to GitHub repository with source code for the publication: Autoencoder-enabled model portability for reducing hyperparameter tuning efforts in side-channel analysis.
The source code uses the Python programming language. Scripts used to run the experiments are in the main directory, while the folder 'src' holds the implementations for hyperparameter tuning, loading of side-channel datasets, etc., providing some abstraction. Scripts starting with 'attack' were used to run experiments, while other scripts were helper scripts for analyzing/reading/plotting results.
Sbatch scripts were used to run experiments with TU Delft servers.
More information can be found in the publication.
- CC-BY-4.0
Reference papers
Mentions
- 1.Author(s): I. Qudsi, A. Herlambang, A. KoeshidayatullahPublished in Middle East Oil, Gas and Geosciences Show (MEOS GEO) by SPE in 202510.2118/227298-ms
- 2.Author(s): Logan Reichling, Ryan Evans, Mabon Ninan, Phuc Mai, Boyang Wang, Yunsi Fei, John M. EmmertPublished in 2025 IEEE International Symposium on Hardware Oriented Security and Trust (HOST) by IEEE in 2025, page: 462-47310.1109/host64725.2025.11050048