Multi-key privacy-preserving deep learning in cloud computing

2017 ◽  
Vol 74 ◽  
pp. 76-85 ◽  
Author(s):  
Ping Li ◽  
Jin Li ◽  
Zhengan Huang ◽  
Tong Li ◽  
Chong-Zhi Gao ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Privacy Preserving

scholarly journals MSCryptoNet: Multi-Scheme Privacy-Preserving Deep Learning in Cloud Computing

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 29344-29354 ◽  
Author(s):  
Owusu-Agyemang Kwabena ◽  
Zhen Qin ◽  
Tianming Zhuang ◽  
Zhiguang Qin
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Privacy Preserving

Privacy preserving multi-party computation delegation for deep learning in cloud computing

2018 ◽  
Vol 459 ◽  
pp. 103-116 ◽  
Author(s):  
Xu Ma ◽  
Fangguo Zhang ◽  
Xiaofeng Chen ◽  
Jian Shen
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Privacy Preserving

Towards Secure and Privacy-Preserving Distributed Deep Learning in Fog-Cloud Computing

2020 ◽  
pp. 1-1
Author(s):  
Yiran Li ◽  
Hongwei Li Guowen Xu ◽  
Tao Xiang ◽  
Xiaoming Huang ◽  
Rongxing Lu
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Privacy Preserving

An Efficient Privacy-Preserving Rank Query over Encrypted Data in Cloud Computing

2012 ◽  
Vol 35 (11) ◽  
pp. 2215 ◽  
Author(s):  
Fang-Quan CHENG ◽  
Zhi-Yong PENG ◽  
Wei SONG ◽  
Shu-Lin WANG ◽  
Yi-Hui CUI
Keyword(s):  
Cloud Computing ◽  
Privacy Preserving ◽  
Encrypted Data

Power information network intrusion detection based on deep learning and cloud computing

2021 ◽  
pp. 1-9
Author(s):  
Xiangbing Zhao ◽  
Jianhui Zhou
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Intrusion Detection ◽  
High Speed ◽  
Information Networks ◽  
Network Intrusion Detection ◽  
Information Network ◽  
Advantages And Disadvantages ◽  
Network Intrusion ◽  
Capture Mechanism

With the advent of the computer network era, people like to think in deeper ways and methods. In addition, the power information network is facing the problem of information leakage. The research of power information network intrusion detection is helpful to prevent the intrusion and attack of bad factors, ensure the safety of information, and protect state secrets and personal privacy. In this paper, through the NRIDS model and network data analysis method, based on deep learning and cloud computing, the demand analysis of the real-time intrusion detection system for the power information network is carried out. The advantages and disadvantages of this kind of message capture mechanism are compared, and then a high-speed article capture mechanism is designed based on the DPDK research. Since cloud computing and power information networks are the most commonly used tools and ways for us to obtain information in our daily lives, our lives will be difficult to carry out without cloud computing and power information networks, so we must do a good job to ensure the security of network information network intrusion detection and defense measures.

Privacy-preserving remote deep-learning-based inference under constrained client-side environment

2021 ◽  
Author(s):  
Amine Boulemtafes ◽  
Abdelouahid Derhab ◽  
Nassim Ait Ali Braham ◽  
Yacine Challal
Keyword(s):  
Deep Learning ◽  
Privacy Preserving ◽  
Client Side
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