Business driven data cross border risk mechanism research

RONG Jingfeng; CHEN Siyu; WANG Yiyang; NIU Jun; LIU Xujie; ZHOU Anshun; FU Anmin; CAO Chunjie; ZHANG Yuqing

doi:10.11959/j.issn.1000-436x.2025105

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Business driven data cross border risk mechanism research

Comprehensive Reviews | 更新时间：2025-07-04

- Business driven data cross border risk mechanism research
- Journal on Communications Vol. 46, Issue 6, Pages: 251-269(2025)
- 作者机构：
  
  1.海南大学网络空间安全学院，海南海口 570228
  2.国家计算机网络入侵防范中心（中国科学院大学），北京 101408
  3.西安电子科技大学网络与信息安全学院，陕西西安 710126
  4.中国移动通信集团海南有限公司，海南海口 570311
  5.南京邮电大学信息与通信学院，江苏南京 210023
  6.中讯邮电咨询设计院有限公司，北京 100089
  7.南京理工大学计算机科学与技术学院，江苏南京 210023
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China(2023YFB3106400)
- DOI：10.11959/j.issn.1000-436x.2025105
  CLC： TP309.2
- Received：27 October 2024，
  
  Revised：2025-03-31，
  
  Published：25 June 2025
- 稿件说明：
移动端阅览
荣景峰,陈思宇,王艺洋等.业务驱动的数据跨境风险机理研究[J].通信学报,2025,46(06):251-269.

RONG Jingfeng,CHEN Siyu,WANG Yiyang,et al.Business driven data cross border risk mechanism research[J].Journal on Communications,2025,46(06):251-269.
荣景峰,陈思宇,王艺洋等.业务驱动的数据跨境风险机理研究[J].通信学报,2025,46(06):251-269. DOI： 10.11959/j.issn.1000-436x.2025105.

RONG Jingfeng,CHEN Siyu,WANG Yiyang,et al.Business driven data cross border risk mechanism research[J].Journal on Communications,2025,46(06):251-269. DOI： 10.11959/j.issn.1000-436x.2025105.

摘要

针对当前数据安全风险机理研究未能充分考虑跨境数据特有的风险形成原因及要素，难以全面揭示跨境数据风险的全貌与内在联系等问题。为此，提出了基于业务驱动的数据跨境风险机理研究。首先，应用Petri网抽象业务流程并收集过程资料数据。然后，基于过程资料数据抽取相关概念范畴并映射成演化网络叶子节点，同时依据风险因果理论构建风险演化网络。在此基础上，分析计算风险演化网络的相关系数，确定风险要素并系统阐释数据跨境风险机理的形成与演化过程。最后以调查问卷和历史数据分析方式验证分析结论，结果表明研究结论符合调研数据统计结果且与历史风险诱因高度契合。总体而言，所提研究可以为数据跨境风险量化评估提供理论支持，并为数据跨境风险应对提供决策依据。

Abstract

Existing research on data security risk mechanisms had not fully accounted for the unique formation causes and elements of cross-border data risks

limiting our understanding of their overall landscape and internal connections. In response

a business-driven approach was proposed to analyze cross-border data risk mechanisms. Firstly

Petri nets were emploied to abstract business processes and collect process data. Then

relevant conceptual categories were extracted and mapped to the leaf nodes of an evolving network. A risk evolution network was constructed based on risk causation theory

and its correlation coefficients were analyzed to identify key risk elements and elucidate the formation and evolution processes of cross-border data risks. Questionnaire surveys and historical data analysis validate the research findings

showing alignment with survey statistics and historical risk drivers. Overall

the proposed research offers theoretical support for the quantitative assessment of cross-border data risks and provides a decision-making basis for their management.

关键词

Keywords

references

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