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Mitigating side channel attacks on FPGA through deep learning and dynamic partial reconfiguration

发表于 2025-04-21 来源 Scientific Reports DOI 10.1038/S41598-025-98473-3

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作者

Sesibhushana Rao Bommana Sreehari Veeramachaneni Syed Ershad MB Srinivas

单位

Department of Electrical & Electronics Engineering,BITS Pilani Hyderabad Campus,500078,Hyderabad,India;Department of Information Technology,Sri Sivasubramaniya展开

Department of Electrical & Electronics Engineering,BITS Pilani Hyderabad Campus,500078,Hyderabad,India;Department of Information Technology,Sri Sivasubramaniya Nadar College of Engineering,600020,Chennai,India;Department of Electronics and Communication Engineering,Aditya University,533437,Kakinada,India

摘要

This paper introduces a framework that combines Deep Learning (DL) models and Dynamic Partial Reconfiguration (DPR) in Field Programmable Gate Arrays 更多..

Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms.

发表于 2025-01-16 来源 Scientific reports DOI 10.1038/S41598-025-86118-4

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作者

Purushottam Singh Prashant Pranav Sandip Dutta

单位

Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India. purushottamsingh@outlook.com.;Department展开

Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India. purushottamsingh@outlook.com.;Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India.

摘要

This research introduces a novel hybrid cryptographic framework that combines traditional cryptographic protocols with advanced methodologies, specifi 更多..

Cryptographic protocols Data augmentation Genetic algorithms Security optimization side-channel attacks WGAN-GP

Cross subkey side channel analysis based on small samples

发表于 2022/4/15 来源 Scientific Reports DOI 10.1038/S41598-022-10279-9

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作者

Hu Fanliang Wang Huanyu Wang Junnian

单位

School of Physics and Electronic Science,Hunan University of Science and Technology,Xiangtan,China;School of EECS,KTH Royal Institute of Technology,Stockholm,Sw展开

School of Physics and Electronic Science,Hunan University of Science and Technology,Xiangtan,China;School of EECS,KTH Royal Institute of Technology,Stockholm,Sweden

摘要

The majority of recently demonstrated Deep-Learning Side-Channel Analysis (DLSCA) use neural networks trained on a segment of traces containing operat 更多..