{"title":"可更新的专用集交集","authors":"S. Badrinarayanan, Peihan Miao, Tiancheng Xie","doi":"10.2478/popets-2022-0051","DOIUrl":null,"url":null,"abstract":"Abstract Private set intersection (PSI) allows two mutually distrusting parties each with a set as input, to learn the intersection of both their sets without revealing anything more about their respective input sets. Traditionally, PSI studies the static setting where the computation is performed only once on both parties’ input sets. We initiate the study of updatable private set intersection (UPSI), which allows parties to compute the intersection of their private sets on a regular basis with sets that also constantly get updated. We consider two specific settings. In the first setting called UPSI with addition, parties can add new elements to their old sets. We construct two protocols in this setting, one allowing both parties to learn the output and the other only allowing one party to learn the output. In the second setting called UPSI with weak deletion, parties can additionally delete their old elements every t days. We present a protocol for this setting allowing both parties to learn the output. All our protocols are secure against semi-honest adversaries and have the guarantee that both the computational and communication complexity only grow with the set updates instead of the entire sets. Finally, we implement our UPSI with addition protocols and compare with the state-of-the-art PSI protocols. Our protocols compare favorably when the total set size is sufficiently large, the new updates are sufficiently small, or in networks with low bandwidth.","PeriodicalId":74556,"journal":{"name":"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","volume":"2022 1","pages":"378 - 406"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Updatable Private Set Intersection\",\"authors\":\"S. Badrinarayanan, Peihan Miao, Tiancheng Xie\",\"doi\":\"10.2478/popets-2022-0051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Private set intersection (PSI) allows two mutually distrusting parties each with a set as input, to learn the intersection of both their sets without revealing anything more about their respective input sets. Traditionally, PSI studies the static setting where the computation is performed only once on both parties’ input sets. We initiate the study of updatable private set intersection (UPSI), which allows parties to compute the intersection of their private sets on a regular basis with sets that also constantly get updated. We consider two specific settings. In the first setting called UPSI with addition, parties can add new elements to their old sets. We construct two protocols in this setting, one allowing both parties to learn the output and the other only allowing one party to learn the output. In the second setting called UPSI with weak deletion, parties can additionally delete their old elements every t days. We present a protocol for this setting allowing both parties to learn the output. All our protocols are secure against semi-honest adversaries and have the guarantee that both the computational and communication complexity only grow with the set updates instead of the entire sets. Finally, we implement our UPSI with addition protocols and compare with the state-of-the-art PSI protocols. Our protocols compare favorably when the total set size is sufficiently large, the new updates are sufficiently small, or in networks with low bandwidth.\",\"PeriodicalId\":74556,\"journal\":{\"name\":\"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium\",\"volume\":\"2022 1\",\"pages\":\"378 - 406\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/popets-2022-0051\",\"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 on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/popets-2022-0051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
私有集合交集(Private set intersection, PSI)允许互不信任的双方各自以一个集合作为输入,在不透露任何有关各自输入集合的信息的情况下,了解其集合的交集。传统上,PSI研究静态设置,其中计算只对双方的输入集执行一次。我们开始研究可更新私有集交集(UPSI),它允许各方定期计算其私有集与也不断更新的集合的交集。我们考虑两个特定的设置。在第一种称为带加法的UPSI设置中,各方可以向其旧设置中添加新元素。在这种情况下,我们构建了两个协议,一个允许双方学习输出,另一个只允许一方学习输出。在第二种称为弱删除UPSI的设置中,各方可以每t天额外删除他们的旧元素。我们为这个设置提供了一个协议,允许双方学习输出。我们所有的协议对半诚实的对手都是安全的,并且保证计算和通信复杂性只随着集合更新而增加,而不是整个集合。最后,我们用附加协议实现我们的UPSI,并与最先进的PSI协议进行比较。当总集大小足够大,新的更新足够小,或者在低带宽的网络中,我们的协议比较有利。
Abstract Private set intersection (PSI) allows two mutually distrusting parties each with a set as input, to learn the intersection of both their sets without revealing anything more about their respective input sets. Traditionally, PSI studies the static setting where the computation is performed only once on both parties’ input sets. We initiate the study of updatable private set intersection (UPSI), which allows parties to compute the intersection of their private sets on a regular basis with sets that also constantly get updated. We consider two specific settings. In the first setting called UPSI with addition, parties can add new elements to their old sets. We construct two protocols in this setting, one allowing both parties to learn the output and the other only allowing one party to learn the output. In the second setting called UPSI with weak deletion, parties can additionally delete their old elements every t days. We present a protocol for this setting allowing both parties to learn the output. All our protocols are secure against semi-honest adversaries and have the guarantee that both the computational and communication complexity only grow with the set updates instead of the entire sets. Finally, we implement our UPSI with addition protocols and compare with the state-of-the-art PSI protocols. Our protocols compare favorably when the total set size is sufficiently large, the new updates are sufficiently small, or in networks with low bandwidth.