15 Papers
57 Citations
Jun Wang is an academic researcher from South Central University for Nationalities. The author has contributed to research in topics: Computer science & Differential privacy. The author has an hindex of 6, co-authored 13 publications.
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Papers
Intelligent data fusion algorithm based on hybrid delay-aware adaptive clustering in wireless sensor networks
TL;DR: Simulation results show that the proposed intelligent data fusion algorithm based on hybrid delay-aware clustering in WSNs can effectively reduce the network delay, network energy consumption, and extend the network lifetime simultaneously.
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A Differentially Private Unscented Kalman Filter for Streaming Data in IoT
Jun Wang,Rongbo Zhu,Shubo Liu +2 more
TL;DR: An unscented Kalman filter based differentially private steaming data share scheme is proposed to protect user privacy for cloud platform in IoT and improve the utility of released data simultaneously.
58
Edge sensing data-imaging conversion scheme of load forecasting in smart grid
TL;DR: A power load prediction scheme based on edge sensing data-imaging conversion (DIC) is proposed to improve the forecasting accuracy in smart cites and society and a DIC-based convolutional neural network (DI-CNN) is presented to implement convolution.
30
Improved Kalman filter based differentially private streaming data release in cognitive computing
TL;DR: An improved Kalman filter based differentially private streaming data release scheme is proposed for privacy requirement of cognitive computing system, and the experimental results show that the proposed scheme outperforms theKalman filter-based method at the same level of privacy preserving.
27
Electromagnetic radiation based continuous authentication in edge computing enabled internet of things
TL;DR: A continuous edge host authentication method is proposed on the basis of electromagnetic radiation which reflects the behavioral characteristics of edge host with heterogeneous hardware and demonstrates the feasibility of the proposed method through analysis of success rate from ten thousand waterfall spectrograms.
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