基于通感算一体融合的5G风筝专网多源数据弹性安全分析方法

包海斌; 史健赟; 张建创; 王伟; 叶燕华; 王任; 从宇; 胡洋洋

doi:10.11959/j.issn.1000-0801.2026002

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基于通感算一体融合的5G风筝专网多源数据弹性安全分析方法

专题：面向6G的通感算一体化 | 更新时间：2026-03-02

- 基于通感算一体融合的5G风筝专网多源数据弹性安全分析方法
- Elastic security analysis method for multi-source data in 5G kite private network based on integration of communication, sensing and computation
- 电信科学 2026年42卷第1期页码：53-64
- 作者机构：
  
  1.国能浙江北仑第一发电有限公司，浙江杭州 315800
  2.中国移动通信集团浙江有限公司宁波分公司，浙江宁波 315000
  3.北京科技大学，北京 100083
- 作者简介：
  
  [ "包海斌（1984- ），男，现就职于国能浙江北仑第一发电有限公司，主要从事电力生产工作。" ]
  [ "史健赟（1982−），男，现就职于国能浙江北仑第一发电有限公司，主要从事电力生产工作。" ]
  [ "张建创（1971- ），男，现就职于国能浙江北仑第一发电有限公司，主要从事电力生产工作。" ]
  [ "王伟（1983- ），男，现就职于国能浙江北仑第一发电有限公司，主要从事电力企业信息化工作。" ]
  叶燕华（1989- ），女，现就职于中国移动通信集团浙江有限公司宁波分公司，主要从事企业信息化工作。
  王任（1982- ），男，现就职于中国移动通信集团浙江有限公司宁波分公司，主要从事5G工业互联网工作。
  从宇（1996- ），男，北京科技大学博士生，主要研究方向为电力无线通信。
  胡洋洋（2003- ），女，北京科技大学硕士生，主要研究方向为电力无线通信。
- 基金信息：
  
  国家能源集团科技创新项目“基于5G风筝专网的弹性安全体系研究与实践项目”(E621000029)
- DOI：10.11959/j.issn.1000-0801.2026002
  中图分类号： TM73;TN929.5
- 收稿：2025-10-02，
  
  修回：2025-11-18，
  
  录用：2025-12-17，
  
  纸质出版：2026-01-20
- 稿件说明：
移动端阅览
包海斌,史健赟,张建创等.基于通感算一体融合的5G风筝专网多源数据弹性安全分析方法[J].电信科学,2026,42(01):53-64.

Bao Haibin,Shi Jianyun,Zhang Jianchang,et al.Elastic security analysis method for multi-source data in 5G kite private network based on integration of communication, sensing and computation[J].Telecommunications Science,2026,42(01):53-64.
包海斌,史健赟,张建创等.基于通感算一体融合的5G风筝专网多源数据弹性安全分析方法[J].电信科学,2026,42(01):53-64. DOI： 10.11959/j.issn.1000-0801.2026002.

Bao Haibin,Shi Jianyun,Zhang Jianchang,et al.Elastic security analysis method for multi-source data in 5G kite private network based on integration of communication, sensing and computation[J].Telecommunications Science,2026,42(01):53-64. DOI： 10.11959/j.issn.1000-0801.2026002.

摘要

随着通信技术向6G演进，通感算一体化已成为新一代电力专网的关键特征。针对5G风筝专网接入电厂生产控制大区场景下，多源数据跨域关联难、动态关联规则挖掘适应性差、实时安全防护不足等问题，提出一种面向5G-Advanced通感算一体专网的多源数据弹性安全分析方法。该方法以5G专网为通信基础，融合传感器采集的感知数据，构建多源数据融合处理框架，实现跨域数据的计算分析。通过融合斯皮尔曼秩相关分析与时序FP-Growth算法，并引入指数衰减时间权重模型，实现了对包含时间约束的安全风险关联规则的挖掘。仿真结果表明，该方法对现有威胁的规则覆盖率有显著提升，且误报率明显下降，能够适配5G风筝专网的动态数据特征与通感算协同需求，为电力行业核心生产业务的安全连续运行提供技术支撑。

Abstract

With the advancement of communication technologies toward 6G

the integration of communication

sensing and computation has become a critical characteristic of next-generation power private networks. In scenarios where 5G kite private networks are deployed in power plant production control areas

challenges including difficulties in cross-domain association of multi-source data

poor adaptability in dynamic association rule mining

and insufficient real-time security protection have been identified. To address these issues

an elastic security analysis method for multi-source data oriented to 5G-Advanced dvanced integrated sensing-communication-computation private networks was proposed. This method leveraged the 5G private network as the communication foundation

with perceptual data collected by sensors being integrated to construct a multi-source data fusion processing framework

enabling computational analysis of cross-domain data. By combining Spearman rank correlation analysis with time-series FP-Growth algorithms and incorporating an exponential decay time-weighted model

security risk association rules with time constraints were effectively mined. Simulation verification shows that this method significantly improves rule coverage for existing threats while effectively reducing the false alarm rate. The method well adapts to the dynamic data characteristics and integrated sensing-communication-computation synergy of 5G kite private networks

providing technical support for the secure and continuous operation of core production services in the power industry.

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