scholarly journals Advanced Deep Learning-Based Computational Offloading for Multilevel Vehicular Edge-Cloud Computing Networks

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 137052-137062 ◽  
Author(s):  
Mashael Khayyat ◽  
Ibrahim A. Elgendy ◽  
Ammar Muthanna ◽  
Abdullah S. Alshahrani ◽  
Soltan Alharbi ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Computational Offloading

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.

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 Cloud Load Estimation with Deep Logarithmic Network for Workload and Time Series Optimization

2021 ◽  
Vol 3 (3) ◽  
pp. 234-248
Author(s):  
N. Bhalaji
Keyword(s):  
Time Series ◽  
Cloud Computing ◽  
Deep Learning ◽  
Extreme Points ◽  
Learning Approach ◽  
Load Estimation ◽  
Learning Method ◽  
Network Computing ◽  
Noise Interference

In recent days, we face workload and time series issue in cloud computing. This leads to wastage of network, computing and resources. To overcome this issue we have used integrated deep learning approach in our proposed work. Accurate prediction of workload and resource allocation with time series enhances the performance of the network. Initially the standard deviation is reduced by applying logarithmic operation and then powerful filters are adopted to remove the extreme points and noise interference. Further the time series is predicted by integrated deep learning method. This method accurately predicts the workload and sequence of resource along with time series. Then the obtained data is standardized by a Min-Max scalar and the quality of the network is preserved by incorporating network model. Finally our proposed method is compared with other currently used methods and the results are obtained.

Attack Detection in Cloud Networks Based on Artificial Intelligence Approaches

2019 ◽  
pp. 63-84
Author(s):  
Zuleyha Yiner ◽  
Nurefsan Sertbas ◽  
Safak Durukan-Odabasi ◽  
Derya Yiltas-Kaplan
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Learning Algorithms ◽  
General Information ◽  
Attack Detection ◽  
Machine Learning Algorithms ◽  
Training Data ◽  
Network Access ◽  
Cloud Infrastructure ◽  
Security Issues

Cloud computing that aims to provide convenient, on-demand, network access to shared software and hardware resources has security as the greatest challenge. Data security is the main security concern followed by intrusion detection and prevention in cloud infrastructure. In this chapter, general information about cloud computing and its security issues are discussed. In order to prevent or avoid many attacks, a number of machine learning algorithms approaches are proposed. However, these approaches do not provide efficient results for identifying unknown types of attacks. Deep learning enables to learning features that are more complex, and thanks to the collection of big data as a training data, deep learning achieves more successful results. Many deep learning algorithms are proposed for attack detection. Deep networks architecture is divided into two categories, and descriptions for each architecture and its related attack detection studies are discussed in the following section of chapter.

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