Computer Science

Computer Science ›› 2025, Vol. 52 ›› Issue (11A): 241200047-8.doi: 10.11896/jsjkx.241200047

• Information Security • Previous Articles     Next Articles

Information Level Inference Method for Data Aggregation Based on Granular Association

LI Jinhui1, CAO Lifeng2, WANG Xiaoqin2, BAI Jinlong2, CHEN Yang2   

  1. 1 Henan Provincial Key Laboratory of Information Security,Zhengzhou 450000,China
    2 China Electronics Technology Group Corporation Seventh Research Institute,Guangzhou 510277,China
  • Online:2025-11-15 Published:2025-11-10

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Abstract: To address the issue of sensitive information leakage through the existence of big data aggregation,this study analyzes the correlation between data deeply and proposes an information level inference method for data aggregation based on granular association.The method mines highly associated data objects based on the dependencies of data attributes,and then deduces the possibility of inferring highly sensitive information from data aggregation when users access the multi-information system based on the fuzzy set possibility measurement of the sensitivity level of the associated attributes of the data objects.This approach aids in establishing access policies for users,controlling the control the analysis of associated data,and reducing the risk of information leakage.

Key words: Data analysis, Granular association, Association rules, Aggregation inference, Information leakage

CLC Number: 

  • TP309
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