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Profiled power analysis attacks using convolutional neural networks with domain knowledge

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Publication:1726696
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DOI10.1007/978-3-030-10970-7_22zbMath1447.94043OpenAlexW2911074137MaRDI QIDQ1726696

Tim Güneysu, Benjamin Hettwer, Stefan Gehrer

Publication date: 20 February 2019

Full work available at URL: https://doi.org/10.1007/978-3-030-10970-7_22

zbMATH Keywords

convolutional neural networksdeep learningside-channel attacks


Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Cryptography (94A60)


Related Items

Learning when to stop: a mutual information approach to prevent overfitting in profiled side-channel analysis


Uses Software

  • Scikit
  • Keras


Cites Work

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  • Power analysis attack: an approach based on machine learning
  • Knowledge-based artificial neural networks
  • Robust profiling for DPA-style attacks
  • Breaking cryptographic implementations using deep learning techniques
  • Analysis and Improvements of the DPA Contest v4 Implementation
  • A Unified Framework for the Analysis of Side-Channel Key Recovery Attacks
  • Convolutional Neural Networks with Data Augmentation Against Jitter-Based Countermeasures
  • Power Analysis Attacks
  • Cryptographic Hardware and Embedded Systems - CHES 2004
  • Template Attacks on Masking—Resistance Is Futile
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