网络与信息安全学报2024，Vol.10Issue(6)：24-36,13.DOI:10.11959/j.issn.2096-109x.2024078
面向多方数据融合分析的隐私计算技术综述
Review of privacy computing techniques for multi-party data fusion analysis
摘要
Abstract
In the data era,threats to personal privacy information in ubiquitous sharing environments are wide-spread,such as apps frequently collecting personal information beyond scope,and big data-enabled price discrimi-nation against frequent customers.The need for multi-party privacy computing for cross-system exchanges is ur-gent.This work focused on the needs of multi-party privacy computing for cross-system exchanges in ubiquitous sharing environments,taking the security sharing and controlled dissemination of private data in multi-party data fusion applications as the starting point,and provided reviews of existing relevant work from the perspectives of multi-party privacy computing,multi-party privacy information sharing control,and multi-party data collaborative secure computing.First,the background and research status of personal privacy information protection in a ubiqui-tous sharing environment were analyzed.Then,the latest domestic and foreign research results in recent years re-garding multi-party privacy computing,multi-party privacy information sharing control,and multi-party data col-laborative security computing were reviewed and comparatively analyzed.Regarding multi-party privacy comput-ing,technologies such as full lifecycle privacy protection,privacy information flow control,and secure exchange of sensitive data were introduced.In terms of multi-party privacy information sharing control,localized control,ex-tended control,and anonymization control techniques were discussed.In the aspect of multi-party data collabora-tive secure computing,commonly used techniques in both academia and industry were discussed.Finally,the chal-lenges and development directions of multi-party privacy computing were prospected.There were still limitations for anonymity,scrambling,or access control-based traditional privacy desensitization measures,cryptography-based measures,and federated learning-based measures,while privacy computing theory provided a computational and information system framework for full-lifecycle protection,which needed to be combined with different appli-cation scenarios to implement full-lifecycle privacy information protection.关键词
隐私计算/隐私信息共享控制/协同安全计算Key words
privacy computing/privacy information sharing control/data collaborative secure computing分类
信息技术与安全科学引用本文复制引用
刘圣龙,黄秀丽,江伊雯,姜嘉伟,田月池,周泽峻,牛犇..面向多方数据融合分析的隐私计算技术综述[J].网络与信息安全学报,2024,10(6):24-36,13.基金项目
国家电网有限公司总部管理科技项目(5108-202218280A-2-393-XG) Science and Technology Project of State Grid Corporation of China(5108-202218280A-2-393-XG) （5108-202218280A-2-393-XG）
