An Industrial Digital Financial Application Platform based on Privacy Computing

In the digital economy era, data information has become an indispensable production factor and the core asset of enterprises. Therefore, the data privacy protection issue is highlighted. Recently, privacy computing technology has become the focus of both academic and industry. The property of data that can be easily replicated leads an exposed information problem. We aim to build a safe, efficient, active and well-established industrial digital financial application platform for privacy computing. First, the user’s preferences, interests and behaviors are generated based on the analysis of their browsing history. Then, add noise or disturbance to the data, after that, the data is processed through the differential privacy algorithm. This platform contains modules such as data acquisition, data encryption and desensitization, differential privacy protection and so on. The platform utilizes a low-coupling and modular design approach. As a result, the data is available but invisible, and the ownership of data is clear. The data sharing is achieved on the premise of security and privacy.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1145/3718391.3718415
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
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An Industrial Digital Financial Application Platform based on Privacy Computing

C You, Xiaobin Zhang, Mingjun Huang, Peng Chen et al.
Privacy-Preserving Technologies in Data
article

An Industrial Digital Financial Application Platform based on Privacy Computing

C You, Xiaobin Zhang, Mingjun Huang, Peng Chen, Bin Liu
article en

Abstract

In the digital economy era, data information has become an indispensable production factor and the core asset of enterprises. Therefore, the data privacy protection issue is highlighted. Recently, privacy computing technology has become the focus of both academic and industry. The property of data that can be easily replicated leads an exposed information problem. We aim to build a safe, efficient, active and well-established industrial digital financial application platform for privacy computing. First, the user’s preferences, interests and behaviors are generated based on the analysis of their browsing history. Then, add noise or disturbance to the data, after that, the data is processed through the differential privacy algorithm. This platform contains modules such as data acquisition, data encryption and desensitization, differential privacy protection and so on. The platform utilizes a low-coupling and modular design approach. As a result, the data is available but invisible, and the ownership of data is clear. The data sharing is achieved on the premise of security and privacy.

Xiamen Tobacco Industry (China) (CN)
Openalex Percentile: Top 72%
Privacy-Preserving Technologies in Data
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