Reinforcement learning-based design of side-channel countermeasures

DOI10.1007/978-3-030-95085-9_9zbMath1499.68059OpenAlexW4226468476MaRDI QIDQ2154063

Lichao Wu, Guilherme Perin, Jorai Rijsdijk

Publication date: 13 July 2022

Full work available at URL: https://doi.org/10.1007/978-3-030-95085-9_9

zbMATH Keywords

reinforcement learningside-channel analysisdeep learningcountermeasures

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Cryptography (94A60) Computer security (68M25)

Cites Work

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• Deep neural network attribution methods for leakage analysis and symmetric key recovery
• On the influence of optimizers in deep learning-based side-channel analysis
• Breaking cryptographic implementations using deep learning techniques
• How to fool a black box machine learning based side-channel security evaluation
• A Unified Framework for the Analysis of Side-Channel Key Recovery Attacks
• An Efficient Method for Random Delay Generation in Embedded Software
• Convolutional Neural Networks with Data Augmentation Against Jitter-Based Countermeasures
• Gradient visualization for general characterization in profiling attacks

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