A secure visual framework for multi-index protection evaluation in networks

Mining the core value of Industrial Internet of Things (IIoT) data safely and reducing the risk of malicious attacks are the inherent requirements of industrial data visualization. Visualization technology has become the main tool for data aggregation, mining and analysis of IIoT data through graphi...

Full description

Saved in:
Bibliographic Details
Published inDigital communications and networks Vol. 9; no. 2; pp. 327 - 336
Main Authors Wu, Xiang, Wang, Huanhuan, Zhang, Yongting, Li, Ruirui
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.04.2023
Institute of Medical Information Security,Xuzhou Medical University,Xuzhou,221000,China%Xuzhou Hengjia Electronic Technology Co.LTD,Xuzhou,221008,China
KeAi Communications Co., Ltd
Subjects
Data mining
Differential privacy
Privacy preserving
Visualization interactive platform
Differential privacy
Privacy preserving
Data mining
Visualization interactive platform
Online AccessGet full text

Cover

More Information
Summary:Mining the core value of Industrial Internet of Things (IIoT) data safely and reducing the risk of malicious attacks are the inherent requirements of industrial data visualization. Visualization technology has become the main tool for data aggregation, mining and analysis of IIoT data through graphical representation. However, visualization technology still has two shortcomings in big data calculation and analysis scenarios. On the one hand, visual results will lead to the disclosure of sensitive privacy. On the other hand, most visualization tools can't provide an interactive framework for users to select the suitable solutions. To address these problems, we present an open accessible Visual framework based on Differential Privacy theory (VisDP), which provides Multi-index Quantitative comprehensive Evaluation technology (MQE) for data mining results. Considering the advantages of interactive mechanism, VisDP provides rich optional schemes, including the operating web, calling API and the downloading SDK. Finally, we verify the availability and privacy of MQE through mathematical proofs, analyze the hospital medical waste detection system that actually applies the framework, and the experimental results have showed the effectiveness and practicality of the proposed platform.
ISSN:2352-8648
2468-5925
2352-8648
DOI:10.1016/j.dcan.2022.05.007