山西大学学报（自然科学版）2024，Vol.47Issue(6)：1211-1220,10.DOI:10.13451/j.sxu.ns.2023117
基于隐私信息检索的大规模用电增信查询方法
Privacy Information Retrieval Based Credit Inquiry for Large-scale Electricity Users
摘要
Abstract
Electricity usage-based credit report is an important way for enhancing the query accuracy of enterprises'credit conditions.However,there are two main problems in existing credit inquiry service.The first problem is that existing methods do not protect the inquiry preference,which is the private information.The second is that existing private information retrieval method cannot be extended to larger-scale database due to the poor efficiency.To address the above problems,a novel inquiry method named Effi-Retrieval was proposed to simultaneously ensure the inquiry security and promote its efficiency.Particularly,Paillier homomorphic encryption and oblivious polynomial calculation were used to ensure the security of inquiry.Optimal binning strategy with k-anonymity method and hash mapping were used to achieve the personalized privacy requirements of the query party in practice.The complexity of privacy information retrieval was reduced from the exponential function of the database size to the anonymity parameter k.Finally,the security analysis of Effi-Retrieval was presented and numerical experiments were conducted to show the impacts of user privacy requirements and affordable fee on communication overhead.We used the Paillier homomorphic encryption library of Python to simulate the interaction between the client and the server on the same host,and conducted experiments using the Credit Card dataset provided by the FATE open-source federated learning platform.Given database consists of at least 300 items encrpyted by 8 192 key bits,experimental results showed that compared with the traditional method without binning strategy,the encryption polynomial construction time of Effi-Retrieval can be reduced by more than 50%,and compared with the query algorithm without k-anonymity method,the retrieval time can be reduced by at least 30%.关键词
电力增信查询/隐私信息检索/不经意多项式计算/k-匿名/通信开销Key words
power credit enhancement inquiry/privacy information retrieval/oblivious polynomial computation/k-anonymity/com-munication cost分类
信息技术与安全科学引用本文复制引用
李辉,黄祖源,田园,毛正雄,赵鹏,任雪斌,李亚男..基于隐私信息检索的大规模用电增信查询方法[J].山西大学学报（自然科学版）,2024,47(6):1211-1220,10.基金项目
云南电网科技项目(YNKJXM20210141) （YNKJXM20210141）
