TY - GEN
T1 - Multi-Party Private Set Intersection
T2 - 3rd International Conference on Cryptography, Network Security and Communication Technology, CNSCT 2024
AU - Su, Jiuheng
AU - Chen, Zhili
AU - Yang, Xiaomin
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s).
PY - 2024/1/19
Y1 - 2024/1/19
N2 - We present a new circuit-based protocol for multi-party private set intersection (PSI) that allows m parties to compute the intersection of their datasets without revealing any additional information about the items outside the intersection. Building upon the two-party Sort-Compare-Shuffle (SCS) protocol, we seamlessly extend it to a multi-party setting. Demonstrating its practicality through implementation, our protocol exhibits acceptable performance. Specifically, with 7 parties, each possessing a set size of {2}^{12}$ ?>, our protocol completes in just 19 seconds. Moreover, circuit-based protocols like ours have an advantage over using custom protocols to perform more complex computation. We substantiate this advantage by incorporating a module for calculating the Jaccard similarity metric of the private sets which can be used in the application domain of network traffic analysis for anomaly detection. This extension showcases the versatility of our protocol beyond set intersection computations, demonstrating its efficacy in preserving privacy while efficiently identifying abnormal patterns in network flow.
AB - We present a new circuit-based protocol for multi-party private set intersection (PSI) that allows m parties to compute the intersection of their datasets without revealing any additional information about the items outside the intersection. Building upon the two-party Sort-Compare-Shuffle (SCS) protocol, we seamlessly extend it to a multi-party setting. Demonstrating its practicality through implementation, our protocol exhibits acceptable performance. Specifically, with 7 parties, each possessing a set size of {2}^{12}$ ?>, our protocol completes in just 19 seconds. Moreover, circuit-based protocols like ours have an advantage over using custom protocols to perform more complex computation. We substantiate this advantage by incorporating a module for calculating the Jaccard similarity metric of the private sets which can be used in the application domain of network traffic analysis for anomaly detection. This extension showcases the versatility of our protocol beyond set intersection computations, demonstrating its efficacy in preserving privacy while efficiently identifying abnormal patterns in network flow.
KW - Private Set Intersection
KW - Secure Multi-party Computation
UR - https://www.scopus.com/pages/publications/85196066154
U2 - 10.1145/3673277.3673340
DO - 10.1145/3673277.3673340
M3 - 会议稿件
AN - SCOPUS:85196066154
T3 - ACM International Conference Proceeding Series
SP - 361
EP - 366
BT - Proceedings of 2024 3rd International Conference on Cryptography, Network Security and Communication Technology, CNSCT 2024
PB - Association for Computing Machinery
Y2 - 19 January 2024 through 21 January 2024
ER -