Achieving Adaptive Privacy-Preserving Graph Neural Networks Training in Cloud Environment

Yanli Yuan, Dian Lei, Qing Fan, Keli Zhao, Liehuang Zhu, Chuan Zhang*

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

With the widespread adoption of Graph Neural Network (GNN) technology in industry, concerns regarding graph data privacy have become increasingly prominent. Differential privacy has been demonstrated as an effective method to ensure privacy in graph learning. However, existing differential privacy-based GNN methods often overlook the individual privacy protection needs of users, offering uniform privacy guarantees to all. This approach can result in either over-protection or insufficient protection for certain users. To address this issue, we propose an adaptive privacy-preserving GNN training method that accommodates the varying privacy requirements of nodes while achieving high model training accuracy. Specifically, APPGNN allocates adaptive privacy budgets based on individual user privacy needs. Additionally, to mitigate the impact of noise on data utility, APPGNN incorporates a weighted neighborhood aggregation mechanism to enhance GNN model accuracy. Theoretical analysis indicates that APPGNN provides adaptive privacy protection while ensuring ϵ-differential privacy on node data. Experimental evaluations on four real-world graph datasets validate the effectiveness of APPGNN.

源语言英语
主期刊名2024 IEEE 12th International Conference on Information and Communication Networks, ICICN 2024
出版商Institute of Electrical and Electronics Engineers Inc.
181-186
页数6
ISBN(电子版)9798350355802
DOI
出版状态已出版 - 2024
活动12th IEEE International Conference on Information and Communication Networks, ICICN 2024 - Guilin, 中国
期限: 21 8月 202424 8月 2024

出版系列

姓名2024 IEEE 12th International Conference on Information and Communication Networks, ICICN 2024

会议

会议12th IEEE International Conference on Information and Communication Networks, ICICN 2024
国家/地区中国
Guilin
时期21/08/2424/08/24

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引用此

Yuan, Y., Lei, D., Fan, Q., Zhao, K., Zhu, L., & Zhang, C. (2024). Achieving Adaptive Privacy-Preserving Graph Neural Networks Training in Cloud Environment. 在 2024 IEEE 12th International Conference on Information and Communication Networks, ICICN 2024 (页码 181-186). (2024 IEEE 12th International Conference on Information and Communication Networks, ICICN 2024). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICICN62625.2024.10761771