{"title":"基于随机响应的隐私保护数据挖掘研究","authors":"L. Xiaoping, Li Jianfeng, Song Haina","doi":"10.1145/3407703.3407727","DOIUrl":null,"url":null,"abstract":"Data mining has played an active role in some deep-level applications, but at the same time, it also brings many problems in information security and privacy protection. The association rule mining algorithm based on randomized response (RR) protects private information to a certain extent. However, because all the disturbed data in the data interference strategy based on randomized response are directly related to the real original data, the effect of privacy protection is not obvious. Aiming at this problem, this paper proposes a more effective privacy protection method in association rule mining. Based on the existing association rule mining model, a suitable perturbation strategy is designed to reduce the interference between the perturbed data and the original data. Relevance, without affecting the accuracy of mining, further enhance the degree of privacy protection of the mechanism.","PeriodicalId":284603,"journal":{"name":"Proceedings of the 2020 Artificial Intelligence and Complex Systems Conference","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Research on Privacy Preserving Data Mining Based on Randomized Response\",\"authors\":\"L. Xiaoping, Li Jianfeng, Song Haina\",\"doi\":\"10.1145/3407703.3407727\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data mining has played an active role in some deep-level applications, but at the same time, it also brings many problems in information security and privacy protection. The association rule mining algorithm based on randomized response (RR) protects private information to a certain extent. However, because all the disturbed data in the data interference strategy based on randomized response are directly related to the real original data, the effect of privacy protection is not obvious. Aiming at this problem, this paper proposes a more effective privacy protection method in association rule mining. Based on the existing association rule mining model, a suitable perturbation strategy is designed to reduce the interference between the perturbed data and the original data. Relevance, without affecting the accuracy of mining, further enhance the degree of privacy protection of the mechanism.\",\"PeriodicalId\":284603,\"journal\":{\"name\":\"Proceedings of the 2020 Artificial Intelligence and Complex Systems Conference\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 Artificial Intelligence and Complex Systems Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3407703.3407727\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 Artificial Intelligence and Complex Systems Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3407703.3407727","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Privacy Preserving Data Mining Based on Randomized Response
Data mining has played an active role in some deep-level applications, but at the same time, it also brings many problems in information security and privacy protection. The association rule mining algorithm based on randomized response (RR) protects private information to a certain extent. However, because all the disturbed data in the data interference strategy based on randomized response are directly related to the real original data, the effect of privacy protection is not obvious. Aiming at this problem, this paper proposes a more effective privacy protection method in association rule mining. Based on the existing association rule mining model, a suitable perturbation strategy is designed to reduce the interference between the perturbed data and the original data. Relevance, without affecting the accuracy of mining, further enhance the degree of privacy protection of the mechanism.