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...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.展开更多
基金supported by the National Key Research and Development Program of China under Grant No.2020YFC2006600the National Natural Science Foundation of China under Grant No.62003291the National Science and Technology Foundation Project under Grant No.2019FY100100,and the QingLan Project.
文摘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.
