Efficient Private Set Intersection Cardinality Protocol in the Reverse Unbalanced Setting

DOI码：

10.1007/978-3-031-22390-7

发表刊物：

Information Security: 25th International Conference, ISC 2022, Bali, Indonesia, December 18–22, 2022, Proceedings

刊物所在地：

Bali, Indonesia

关键字：

Private set intersection cardinality, Reverse unbalanced scenario, Hash-prefix filter, Private information retrieval, Cuckoo filter

摘要：

Private set intersection cardinality (PSI-CA) is a variant of private set intersection (PSI) that allows two parties, the sender and the receiver, to compute the cardinality of the intersection without leaking anything more to the other party. It’s one of the best-studied applications of secure computation, and many PSI-CA protocols in balanced or unbalanced scenarios have been proposed. Generally, unbalanced scenario means that the private set size of the receiver is significantly smaller than that of the sender. This paper mainly focuses on a new scenario in which the receiver’s set size (client) is much larger than that of the sender (server) called the reverse unbalanced scenario. We study PSI-CA protocols that are secure against semi-honest adversaries, using the Hash-Prefix filter to effectively reduce the computation and communication overhead. We greatly optimize the previous unbalanced PSI-CA protocol and construct a reverse unbalanced PSI-CA protocol. In addition, we introduce private information retrieval (PIR) to resist the privacy leakage of the Hash-Prefix filter. By implementing all protocols on the same platform, we compare the protocols’ performance theoretically and experimentally. Combined with the Cuckoo filter, elliptic curve and multi-threading, the computational and communication efficiency of our protocol is 26.87\texttimes{} and 8.48\texttimes{} higher than the existing unbalanced PSI-CA protocols. By setting sets with significant differences in size, we also prove the feasibility of our protocol in anonymous identity authentication.

合写作者：

Ying Gao

第一作者：

Hanyu Li

论文类型：

会议论文

通讯作者：

Ying Gao

页面范围：

20–39

ISSN号：

978-3-031-22389-1

是否译文：

否

发表时间：

2022-12-09