基于增强关系图卷积网络的数据违规转售检测方法

王宇翔; 张玲翠; 侯雨桥; 杨倩; 牛犇

doi:10.11959/j.issn.1000-436x.2026083

Chinese

您当前的位置：

首页 >

文章列表页 >

基于增强关系图卷积网络的数据违规转售检测方法

学术论文 | 更新时间：2026-05-07

- 基于增强关系图卷积网络的数据违规转售检测方法
- Illicit data resale detection method via an enhanced relational graph convolutional network
- 通信学报 2026年47卷第4期页码：113-125
- 作者机构：
  
  1.中国科学院信息工程研究所，北京 100085
  2.中国科学院大学网络空间安全学院，北京 100049
  3.网络空间安全防御全国重点实验室，北京 100085
- 作者简介：
  
  [ "王宇翔（1991- ），女，山西吕梁人，博士，中国科学院信息工程研究所工程师，主要研究方向为数据安全。" ]
  [ "张玲翠（1986- ），女，河北故城人，博士，中国科学院信息工程研究所高级工程师，主要研究方向为网络与系统安全、数据安全。" ]
  [ "侯雨桥（1989- ），女，北京人，博士，中国科学院信息工程研究所工程师，主要研究方向为数据安全。" ]
  [ "杨倩（1989- ），女，山东聊城人，博士，中国科学院信息工程研究所工程师，主要研究方向为数据安全。" ]
  [ "牛犇（1984- ），男，陕西西安人，博士，中国科学院信息工程研究所研究员、博士生导师，主要研究方向为隐私计算、数据安全。" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2023YFB3106505);国家自然科学基金资助项目(U24A20240;62441226)
- DOI：10.11959/j.issn.1000-436x.2026083
  中图分类号： TN92
- 收稿：2026-02-02，
  
  修回：2026-03-22，
  
  录用：2026-03-26，
  
  纸质出版：2026-04-20
- 稿件说明：
移动端阅览
王宇翔,张玲翠,侯雨桥等.基于增强关系图卷积网络的数据违规转售检测方法[J].通信学报,2026,47(04):113-125.

Wang Yuxiang,Zhang Lingcui,Hou Yuqiao,et al.Illicit data resale detection method via an enhanced relational graph convolutional network[J].Journal on Communications,2026,47(04):113-125.
王宇翔,张玲翠,侯雨桥等.基于增强关系图卷积网络的数据违规转售检测方法[J].通信学报,2026,47(04):113-125. DOI： 10.11959/j.issn.1000-436x.2026083.

Wang Yuxiang,Zhang Lingcui,Hou Yuqiao,et al.Illicit data resale detection method via an enhanced relational graph convolutional network[J].Journal on Communications,2026,47(04):113-125. DOI： 10.11959/j.issn.1000-436x.2026083.

摘要

为解决数据流通交易场景下的数据违规转售问题，基于交易上下文信息相似度和交易因果顺序约束，对关系图卷积网络的消息传递和特征聚合过程进行改进，提出一种增强关系图卷积网络模型，可有效学习复杂交易关系下的违规转售行为特征。基于该模型设计一种数据违规转售检测方法，预测数据交易拓扑图中节点是否为违规转售交易节点。构造带有违规转售样本的模拟数据交易数据集并展开对比实验，结果证明了所提方法的有效性。

Abstract

Illicit data resale in data trading scenarios exhibited strong concealment and was difficult to detect. An enhanced relational graph convolutional network was proposed by optimizing message passing and feature aggregation with transaction contextual similarity and causal temporal order constraints

enabling effective representation of illicit resale behaviors under complex transaction relations. Based on this model

a detection method was developed to predict the existence of illicit resale behaviors in transaction topology graphs. A simulated data trading dataset containing anomalous resale samples was constructed

and comparative experiments were performed. The results indicate that the proposed method provides an effective solution for illicit data resale detection in data trading scenarios.

关键词

Keywords

references

GB/T 37932-2025 数据安全技术数据交易服务安全要求 [S ] .

GB/T 37932-2025 Data security technology—security requirements for data transaction service [S ] .

李凤华 , 李晖 , 牛犇 , 等 . 数据要素流通与安全的研究范畴与未来发展趋势 [J ] . 通信学报 , 2024 , 45 ( 5 ): 1 - 11 .

Li F H , Li H , Niu B , et al . Research category and future development trend of data elements circulation and security [J ] . Journal on Communications , 2024 , 45 ( 5 ): 1 - 11 .

国家数据局 . 2024年全国数据市场交易规模超1600亿元 [EB ] . ( 2025-04-02 )[ 2026-01-29 ] .

National Data Administration . China’s 2024 Data market transaction volume exceeded 160 billion yuan [EB ] . ( 2025-04-02 )[ 2026-01-29 ] .

华为技术有限公司 . 智能世界2035 [EB ] . ( 2025-09 )[ 2026-01-29 ] .

Huawei . Intelligent world 2035 [EB ] . ( 2025-09 )[ 2026-01-29 ] .

Zhang J Y , Bi Y R , Cheng M Y , et al . A survey on data markets [PP ] . V1 . ( 2024-11-09 )[ 2026-02-02 ] . arXiv: arXiv. 2411 . 07267 .

王利明 . 数据何以确权 [J ] . 法学研究 , 2023 , 45 ( 4 ): 56 - 73 .

Wang L M . Confirmation of data rights: why and how [J ] . Chinese Journal of Law , 2023 , 45 ( 4 ): 56 - 73 .

Jung T , Li X Y , Huang W C , et al . AccountTrade: accountability against dishonest big data buyers and sellers [J ] . IEEE Transactions on Information Forensics and Security , 2019 , 14 ( 1 ): 223 - 234 .

Gupta P , Dedeoglu V , Kanhere S S , et al . TrailChain: Traceability of data ownership across blockchain-enabled multiple marketplaces [J ] . Journal of Network and Computer Applications , 2022 , 203 : 103389 .

Sahoo S , Halder R . Traceability and ownership claim of data on big data marketplace using blockchain technology [J ] . Journal of Information and Telecommunication , 2021 , 5 ( 1 ): 35 - 61 .

Dai W Q , Dai C K , Choo K R , et al . SDTE: a secure blockchain-based data trading ecosystem [J ] . IEEE Transactions on Information Forensics and Security , 2020 , 15 : 725 - 737 .

Chen F , Wang J H , Jiang C K , et al . Blockchain based non-repudiable IoT data trading: simpler, faster, and cheaper [C ] // Proceedings of the IEEE INFOCOM 2022 - IEEE Conference on Computer Communications . Piscataway : IEEE Press , 2022 : 1958 - 1967 .

Motie S , Raahemi B . Financial fraud detection using graph neural networks: a systematic review [J ] . Expert Systems with Applications , 2024 , 240 : 122156 .

Dou Y T , Liu Z W , Sun L , et al . Enhancing graph neural network-based fraud detectors against camouflaged fraudsters [C ] // Proceedings of the 29th ACM International Conference on Information & Knowledge Management . New York : ACM Press , 2020 : 315 - 324 .

Liu Y , Ao X , Qin Z D , et al . Pick and choose: a GNN-based imba-lanced learning approach for fraud detection [C ] // Proceedings of the Web Conference 2021 . New York : ACM Press , 2021 : 3168 - 3177 .

Xiang S , Zhu M Z , Cheng D W , et al . Semi-supervised credit card fraud detection via attribute-driven graph representation [J ] . Procee-dings of the AAAI Conference on Artificial Intelligence , 2023 , 37 ( 12 ): 14557 - 14565 .

Kipf T N , Welling M . Semi-supervised classification with graph convolutional networks [PP ] . V4 . ( 2017-02-22 )[ 2026-02-02 ] . arXiv:arXiv. 1609 . 02907 .

Weng Y P , Chen X , Chen L , et al . GAIN: graph attention & interaction network for inductive semi-supervised learning over large-scale graphs [J ] . IEEE Transactions on Knowledge and Data Engineering , 2022 , 34 ( 9 ): 4257 - 4269 .

Wang H W , Hooi B , He D , et al . EGNN-ad: an effective graph neural network-based approach forAnomaly detection onEdge-Attributed graphs [C ] // Database Systems for Advanced Applications . Berlin : Springer , 2024 : 321 - 331 .

Song C C , Lin X X , Shen H Y , et al . UniFORM: towards unified framework for anomaly detection on graphs [J ] . Proceedings of the AAAI Conference on Artificial Intelligence , 2025 , 39 ( 12 ): 12559 - 12567 .

Duan X , Yan B , Dong A , et al . Phishing frauds detection based on graph neural network on Ethereum [C ] // Proceedings of the 17th International Conference on Wireless Algorithms, Systems, and Applications . Berlin : Springer , 2022 : 351 - 363 .

Hu X X , Chen H T , Zhang J J , et al . GAT-COBO: cost-sensitive graph neural network for telecom fraud detection [J ] . IEEE Transactions on Big Data , 2024 , 10 ( 4 ): 528 - 542 .

Schlichtkrull M , Kipf T N , Bloem P , et al . Modeling relational data with graph convolutional networks [C ] // The Semantic Web . Berlin : Springer , 2018 : 593 - 607 .

Mitra R , Dongre A , Dangare P , et al . Knowledge graph driven credit risk assessment for micro, small and medium-sized enterprises [J ] . International Journal of Production Research , 2024 , 62 ( 12 ): 4273 - 4289 .

Jiang C X , Zheng J Y , Xu Q F . Mapping creditworthiness for Chinese small and medium-sized enterprises: integrating knowledge graphs and graph neural networks [J ] . Applied Intelligence , 2026 , 56 ( 1 ): 46 .

Li W , Bao R H , Harimoto K , et al . Modeling the stock relation with graph network for overnight stock movement prediction [C ] // Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence . San Francisco : Morgan Kaufmann , 2020 : 4541 - 4547 .

Sionek A . Brazilian e-commerce public dataset by Olist [EB ] . ( 2018 )[ 2026-01-29 ] .

Rayana S , Akoglu L . Collective opinion spam detection: bridging review networks and metadata [C ] // Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York : ACM Press , 2015 : 985 - 994 .

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于多尺度卷积和通道注意力机制的网络流量异常检测方法

基于CNN-BiLSTM-Attention融合模型的差分隐私轨迹重构攻击

基于深度残差定点网络的太赫兹UM-MIMO系统信道估计算法

MDA-MIM：一种融合多尺度特征与双重注意力机制的雷达回波图预测模型