Multi-Source Heterogeneous Data Collaboration via Private Set Intersection

doi:10.3969/j.issn.1671-1122.2023.08.008

Abstract

Abstract:

The main point of multi-source heterogeneous data fusion is the low value density and dispersion of data. The multi-source heterogeneity of data increases the difficulty of data aggregation, leading to extreme fragmentation of data value, making data fusion methods to face multi-source heterogeneous big data with no target, and unable to effectively correlate data with fragmented value. Private Set Intersection (PSI) not only enables data providers to provide data with peace of mind, but also effectively integrates the value of heterogeneous data from multiple sources, and mines effective data to carry out data fusion work as a new tool. To this end, the article gave three new ideas for the fusion of heterogeneous data from multiple sources with respect to three types of problems: integration of heterogeneous data, multiple sources of data, and parallel processing of large-scale data.

Key words: private set intersection, intelligence analysis

CLC Number:

TP309

DING Jiang, ZHANG Guoyan, WEI Zichong, WANG Mei. Multi-Source Heterogeneous Data Collaboration via Private Set Intersection[J]. Netinfo Security, 2023, 23(8): 86-98.

Figures/Tables 1

References 69

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