Design and Implementation of Side Channel Attack Based on Deep Learning LSTM
Author:
Affiliation:
1. Center for Cyber Security, Universiti Kebangsaan Malaysia,Faculty of Information Science and Technology,Bangi,Malaysia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10223594/10223477/10223652.pdf?arnumber=10223652
Reference21 articles.
1. Tandem Deep Learning Side-Channel Attack Against FPGA Implementation of AES
2. COVID-19 health data analysis and personal data preserving: A homomorphic privacy enforcement approach
3. ALScA: A Framework for Using Auxiliary Learning Side-Channel Attacks to Model PUFs
4. Deep-Learning-Based Side-Channel Analysis of Block Cipher PIPO With Bitslice Implementation
5. EM/Power Side-Channel Attack: White-Box Modeling and Signature Attenuation Countermeasures
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1. Design of Deep Learning Technique Based Side Channel Attack Analysis for System on Chips;INTERNATIONAL JOURNAL OF PROFESSIONAL STUDIES;2024
2. Efficient Convolutional Neural Network Based Side Channel Attacks Based on AES Cryptography;2023 IEEE 21st Student Conference on Research and Development (SCOReD);2023-12-13
3. Optimization Technique for Deep Learning Methodology on Power Side Channel Attacks;2023 33rd International Telecommunication Networks and Applications Conference;2023-11-29
4. Detection of Crucial Power Side Channel Data Leakage in Neural Networks;2023 33rd International Telecommunication Networks and Applications Conference;2023-11-29
5. Design of Lightweight Cryptography based Deep Learning Model for Side Channel Attacks;2023 33rd International Telecommunication Networks and Applications Conference;2023-11-29
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