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A Comprehensive Survey on the Non-Invasive Passive Side-Channel Analysis [PDF]
Sensors, 2022 Side-channel analysis has become a widely recognized threat to the security of cryptographic implementations. Different side-channel attacks, as well as countermeasures, have been proposed in the literature.
Petr Socha +2 more
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Side channel analysis based on feature fusion network. [PDF]
PLoS ONE, 2022 Various physical information can be leaked while the encryption algorithm is running in the device. Side-channel analysis exploits these leakages to recover keys.
Feng Ni +4 more
doaj +2 more sources
Side Channel Analysis of SPECK Based on Transfer Learning [PDF]
Sensors, 2022 Although side-channel attacks based on deep learning are widely used in AES encryption algorithms, there is little research on lightweight algorithms. Lightweight algorithms have fewer nonlinear operations, so it is more difficult to attack successfully.
Qingqing Zhang +4 more
doaj +2 more sources
Hybrid Threshold Denoising Framework Using Singular Value Decomposition for Side-Channel Analysis Preprocessing [PDF]
Entropy, 2023 The traces used in side-channel analysis are essential to breaking the key of encryption and the signal quality greatly affects the correct rate of key guessing.
Yuanzhen Wang +7 more
doaj +2 more sources
Cross subkey side channel analysis based on small samples [PDF]
Scientific Reports, 2022 The majority of recently demonstrated Deep-Learning Side-Channel Analysis (DLSCA) use neural networks trained on a segment of traces containing operations only related to the target subkey.
Fanliang Hu, Huanyu Wang, Junnian Wang
doaj +2 more sources
Weakly Profiling Side-channel Analysis [PDF]
Transactions on Cryptographic Hardware and Embedded SystemsProfiling side-channel analysis, recognized for its robust attack performance in worst-case scenarios, necessitates adversaries to have a cloned device for profiling measurements and secret information for data labeling.
Lichao Wu +2 more
doaj +4 more sources
Multi-Leak Deep-Learning Side-Channel Analysis
IEEE Access, 2022 Deep Learning Side-Channel Attacks (DLSCAs) have become a realistic threat to implementations of cryptographic algorithms, such as Advanced Encryption Standard (AES). By utilizing deep-learning models to analyze side-channel measurements, the attacker is
Fanliang Hu, Huanyu Wang, Junnian Wang
doaj +2 more sources
An Enhanced Dataflow Analysis to Automatically Tailor Side Channel Attack Countermeasures to Software Block Ciphers [PDF]
, 2017 Protecting software implementations of block ciphers from side channel attacks is a significant concern to realize secure embedded computation platforms.
Barenghi, Alessandro, Pelosi, Gerardo
core +2 more sources
Side Channel Analysis Attack Based on Deep Learning LSTM [PDF]
Jisuanji gongcheng, 2021 The security of encrypted data is affected by encryption algorithms and encryption devices.The reliability of the encryption devices can be tested by using multiple types of attacks, such as energy analysis.Among different attack methods, the method of ...
WANG Junnian, ZHU Bin, YU Wenxin, WANG Wan, HU Fanliang
doaj +1 more source
SCANN: Side Channel Analysis of Spiking Neural Networks
Cryptography, 2023 Spiking neural networks (SNNs) are quickly gaining traction as a viable alternative to deep neural networks (DNNs). Compared to DNNs, SNNs are computationally more powerful and energy efficient.
Karthikeyan Nagarajan +4 more
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