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AutoEncodersDLSCA

Code underlying the publication: Autoencoder-enabled model portability for reducing hyperparameter tuning efforts in side-channel analysis

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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.

Logo of AutoEncodersDLSCA
Keywords
Autoencoders
Hyperparameter Tuning
Portability
Preprocessing
Side-channel Analysis
transfer learning
Programming languages
License
  • CC-BY-4.0
</>Source code
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Contributors

MK
Marina Krček

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4TU