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Recent advances in deep learning‐based side‐channel analysis

Sunghyun Jin, Suhri Kim, HeeSeok Kim, Seokhie Hong
2020 ETRI Journal  
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

Léo Weissbart, Łukasz Chmielewski, Stjepan Picek, Lejla Batina
2020 Journal of Hardware and Systems Security  
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

Bo Ma, Jinsong Wu, William Liu, Luca Chiaraviglio, Xing Ming
2020 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI)  
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

Muhammad Usman Sana, Zhanli Li, Fawad Javaid, Hannan Bin Liaqat, Muhammad Usman Ali
2021 IEEE Access  
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

Huailai Zhou, Yangqin Guo, Ke Guo
2021 Minerals  
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

Jinsong Xu
2019 Discrete and Continuous Dynamical Systems. Series S  
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

Jinqian Chen, Yong Yan, Shaoyong Guo, Yinlin Ren, Feng Qi, Chi-Hua Chen
2022 Wireless Communications and Mobile Computing  
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]

Runhua Xu, Nathalie Baracaldo, James Joshi
2021 arXiv   pre-print
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

Naila Mukhtar, Mohamad Mehrabi, Yinan Kong, Ashiq Anjum
2018 Applied Sciences  
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

Zhaohe Chen, Ming Tang, Jinghai Li, Leo Yu Zhang
2022 Security and Communication Networks  
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

Shapla Khanam, Ismail Bin Ahmedy, Mohd Yamani Idna Idris, Mohamed Hisham Jaward, Aznul Qalid Bin Md Sabri
2020 IEEE Access  
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]

Saeed Ahmadi
2022 arXiv   pre-print
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

Sergio Saponara, Abdussalam Elhanashi, Qinghe Zheng
2021 IEEE Access  
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

Gregory Epiphaniou, Petros Karadimas, Dhouha Kbaier Ben Ismail, Haider Al-Khateeb, Ali Dehghantanha, Kim-Kwang Raymond Choo
2018 IEEE Internet of Things Journal  
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

Pingping Bing, Wei Liu, Zhihua Zhang
2021 IEEE Access  
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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