TY - GEN
T1 - MDPPC
T2 - 20th Annual International Conference on Privacy, Security and Trust, PST 2023
AU - Yang, Yihao
AU - Dong, Xiaolei
AU - Shen, Jiachen
AU - Cao, Zhenfu
AU - Yang, Yunbo
AU - Zhou, Jun
AU - Fang, Liming
AU - Liu, Zhe
AU - Ge, Chunpeng
AU - Su, Chunhua
AU - Hou, Zongyang
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Private Set Intersection (PSI) is one of the most important functions in secure multiparty computation (MPC). PSI protocols have been a practical cryptographic primitive and there are many privacy-preserving applications based on PSI protocols such as computing conversion of advertising and distributed computation. Private Set Intersection Cardinality (PSI-CA) is a useful variant of PSI protocol. PSI and PSI-CA allow several parties, each holding a private set, to jointly compute the intersection and cardinality, respectively without leaking any additional information. Nowadays, most PSI protocols mainly focus on two-party settings, while in multiparty settings, parties are able to share more valuable information and thus more desirable. On the other hand, with the advent of cloud computing, delegating computation to an untrusted server becomes an interesting problem. However, most existing delegated PSI protocols are unable to efficiently scale to multiple clients. In order to solve these problems, this paper proposes MDPPC, an efficient PSI protocol which supports scalable multiparty delegated PSI and PSI-CA operations. Security analysis shows that MDPPC is secure against semi-honest adversaries and it allows any number of colluding clients. For 15 parties with set size of 220 on server side and 216 on clients side, MDPPC costs only 81 seconds in PSI and 80 seconds in PSI-CA, respectively. The experimental results show that MDPPC has high scalability.
AB - Private Set Intersection (PSI) is one of the most important functions in secure multiparty computation (MPC). PSI protocols have been a practical cryptographic primitive and there are many privacy-preserving applications based on PSI protocols such as computing conversion of advertising and distributed computation. Private Set Intersection Cardinality (PSI-CA) is a useful variant of PSI protocol. PSI and PSI-CA allow several parties, each holding a private set, to jointly compute the intersection and cardinality, respectively without leaking any additional information. Nowadays, most PSI protocols mainly focus on two-party settings, while in multiparty settings, parties are able to share more valuable information and thus more desirable. On the other hand, with the advent of cloud computing, delegating computation to an untrusted server becomes an interesting problem. However, most existing delegated PSI protocols are unable to efficiently scale to multiple clients. In order to solve these problems, this paper proposes MDPPC, an efficient PSI protocol which supports scalable multiparty delegated PSI and PSI-CA operations. Security analysis shows that MDPPC is secure against semi-honest adversaries and it allows any number of colluding clients. For 15 parties with set size of 220 on server side and 216 on clients side, MDPPC costs only 81 seconds in PSI and 80 seconds in PSI-CA, respectively. The experimental results show that MDPPC has high scalability.
KW - Multiparty Computation
KW - Oblivious Pseudorandom Function
KW - Private Set Intersection
UR - https://www.scopus.com/pages/publications/85179549969
U2 - 10.1109/PST58708.2023.10320155
DO - 10.1109/PST58708.2023.10320155
M3 - 会议稿件
AN - SCOPUS:85179549969
T3 - 2023 20th Annual International Conference on Privacy, Security and Trust, PST 2023
BT - 2023 20th Annual International Conference on Privacy, Security and Trust, PST 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 August 2023 through 23 August 2023
ER -