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Recent advances in deep learning‐based side‐channel analysis
2020
ETRI Journal
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In particular, we outline how deep learning is applied to side-channel analysis, based on deep learning architectures and application methods. ...
As side-channel analysis and machine learning algorithms share the same objective of classifying data, numerous studies have been proposed for adapting machine learning to side-channel analysis. ...
Hettwer and others used such attribution methods for leakage analysis, and presented three attribution methods, which are based on the saliency map [81] , layer-wise relevance propagation [82] , and ...
doi:10.4218/etrij.2019-0163
fatcat:lp55bkryirbl7jpkv527kd3dja
Systematic Side-Channel Analysis of Curve25519 with Machine Learning
2020
Journal of Hardware and Systems Security
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Most techniques considered in this work result in potent attacks, and especially the method of choice appears to be convolutional neural networks (CNNs), which can break the first implementation with only ...
The same convolutional neural network demonstrated excellent performance for attacking AES cipher implementations. ...
We investigate the applicability of one visualization technique for deep learning when attacking public-key implementations. ...
doi:10.1007/s41635-020-00106-w
fatcat:wmwwznqpizhkvk6wfbryoneqvm
Combating Hard or Soft Disasters with Privacy-Preserving Federated Mobile Buses-and-Drones based Networks
2020
2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI)
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It is foreseeable the popularity of the mobile edge computing enabled infrastructure for wireless networks in the incoming fifth generation (5G) and future sixth generation (6G) wireless networks. ...
On the other hand, the federated machine learning (FML) methods have been newly developed to address the privacy leakage problems of the traditional machine learning held normally by one centralized organization ...
The hidden layer can be added in Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), which theoretically can draw a connection between neural network pruning and differential privacy ...
doi:10.1109/iri49571.2020.00013
dblp:conf/iri/0008WLCM20
fatcat:zhk6r3l6gvfd5a6jngy5zbt4yy
Enhanced Security in Cloud Computing Using Neural Network and Encryption
2021
IEEE Access
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Results showed that applying neural network training with MORE offers improved accuracy, runtime, and performance. ...
We examined the speech and voice recognition problem and the performance of the proposed method has been validated in MATLAB simulation. ...
Complete key recovery is possible with high probability and very small execution time. ...
doi:10.1109/access.2021.3122938
fatcat:jpnki543zncbnij37pivanhbvi
Seismic Random Noise Attenuation Using a Tied-Weights Autoencoder Neural Network
2021
Minerals
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Subsequently, we designed a robust deep convolutional neural network (CNN), which only depended on the input noise dataset to learn hidden features. ...
Results based on synthetic and real data indicated that the proposed method performs better than other novel denoising methods without loss of signal quality loss. ...
Acknowledgments: We would also like to express our gratitude to the Geomathematics Key Laboratory of Sichuan Province and the Key Lab of Earth Exploration and Information Techniques of the Ministry of ...
doi:10.3390/min11101089
fatcat:gr3duwekzzco3am2vo7g7j3fae
Reversible hidden data access algorithm in cloud computing environment
2019
Discrete and Continuous Dynamical Systems. Series S
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of filtering results are output; the parameters between three anchor nodes and the location of reversible hidden data are measured, and the artificial bee colony optimization neural network is used for ...
improve;through the establishment of authorized institutions, producing key, off-line encryption, online encryption, ciphertext conversion, decrypt ion and other aspects, the security of access data is ...
Data owner randomly selects the key, and calculates the symmetric key sk = H (ck), to encrypts the data with the symmetric key, and generate the data ciphertext CT , and the authentication token T oken ...
doi:10.3934/dcdss.2019084
fatcat:emhn5qs7cnd4rgsgsdq5av2cnu
A System for Trusted Recovery of Data Based on Blockchain and Coding Techniques
2022
Wireless Communications and Mobile Computing
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At the same time, in the power Internet of Things environment, reliable data is essential for data use and accurate analysis. ...
It has good security and real-time performance. Meanwhile, it reduces the network and storage resource overhead in the data backup and recovery process. ...
Acknowledgments This work is supported by the Key Science and Technology Project of State Grid Corporation of China, No. 5700202019374A0000. ...
doi:10.1155/2022/8390241
fatcat:fqguovezevf2fcloie4ptdg5hy
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
[article]
2021
arXiv
pre-print
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Such a need for and the use of huge volumes of data raise serious privacy concerns because of the potential risks of leakage of highly privacy-sensitive information; further, the evolving regulatory environments ...
challenges and a research roadmap for future research in PPML area. ...
the inference phase for deep neural networks, as exemplified in [88, 126] . ...
arXiv:2108.04417v2
fatcat:pmxmsbs2gvh6nd4jadcz4dnsrq
Machine-Learning-Based Side-Channel Evaluation of Elliptic-Curve Cryptographic FPGA Processor
2018
Applied Sciences
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This paper formalizes the methodology for preparing an input dataset for further analysis using machine-learning-based techniques to classify the secret-key bits. ...
The results further show the parameter tuning and the amount of time required for building the machine-learning models. ...
To perform the side-channel-based key-recovery analysis, various statistical and mathematical methods are used [11] [12] [13] [14] [15] [16] . ...
doi:10.3390/app9010064
fatcat:t7txvk2ig5fulp5kg575pcei3e
Inversion Attacks against CNN Models Based on Timing Attack
2022
Security and Communication Networks
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Model confidentiality attacks on convolutional neural networks (CNN) are becoming more and more common. ...
We study the time leakage of CNN running on the SoC (system on-chip) system and propose a reverse method based on side-channel attack. ...
Acknowledgments is research was supported by the National Natural Science Foundation of China under Grant no. 61972295, the Wuhan Science and Technology Project Application Foundation Frontier Special ...
doi:10.1155/2022/6285909
fatcat:iqwcgm3k2fbtnbfvod4434uh3m
A Survey of Security Challenges, Attacks Taxonomy and Advanced Countermeasures in the Internet of Things
2020
IEEE Access
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The authors carried out a leakage assessment and characterized noise using statistical methods. They provided key recovery using Advanced Encryption Standard (AES). ...
The authors of [177] , [178] initiate a jamming attack using a deep neural network and proposed mitigation methods for this type of attack. ...
doi:10.1109/access.2020.3037359
fatcat:pw4fsmelmjgc5anm7hp537l63e
Privacy-Preserving Cloud Computing: Ecosystem, Life Cycle, Layered Architecture and Future Roadmap
[article]
2022
arXiv
pre-print
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Cloud computing is important because it allows for scalability, adaptability, and improved security. ...
This paper helps to identify existing trends by establishing a layered architecture along with a life cycle and an ecosystem for privacy-preserving cloud systems in addition to identifying the existing ...
that is a hierarchical Pythagorean fuzzy deep neural network. ...
arXiv:2204.11120v1
fatcat:tx75pckegjgqxg6tiibptiazbi
Recreating Fingerprint Images by Convolutional Neural Network Autoencoder Architecture
2021
IEEE Access
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Deep learning, especially Convolutional Neural Network (CNN) has made a tremendous success in the field of computer vision for pattern recognition. ...
The trained architecture was tested and compared to the other state-of-the-art methods. ...
ACKNOWLEDGMENT We thank the Islamic Development Bank for the support of the Ph.D. work of A. Elhanashi and the "Dipartimenti di Eccellenza -Crosslab" project by MIUR. ...
doi:10.1109/access.2021.3124746
fatcat:twzkbnr2lzafnnokw3oq6o4jua
Nonreciprocity Compensation Combined With Turbo Codes for Secret Key Generation in Vehicular Ad Hoc Social IoT Networks
2018
IEEE Internet of Things Journal
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The physical attributes of the dynamic vehicle-to-vehicle (V2V) propagation channel can be utilised for the generation of highly random and symmetric cryptographic keys. ...
This has to be addressed prior to the symmetric key generation which is inherently important in social Internet of Things (IoT) networks, including in adversarial settings (e.g. battlefields). ...
ACKNOWLEDGMENT This work was partially funded by the Defence Science and Technology Laboratory (DSTL), under contract CDE 41130. ...
doi:10.1109/jiot.2017.2764384
fatcat:a7w64un4f5g4fbn2k2irgyxfbi
DeepCEDNet: An Efficient Deep Convolutional Encoder-Decoder Networks for ECG Signal Enhancement
2021
IEEE Access
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Chih-Yu Hsu and four anonymous reviewers for their constructive comments that improve the paper greatly. ...
robustness of deep neural network. ...
CNN and FCN are two classic neural networks, and have been widely applied in ECG signal analysis [27] , thus, they are employed for comparison. ...
doi:10.1109/access.2021.3072640
fatcat:4aewm3hqc5bsflyoopefdnecxq
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