Practical and Malicious Multiparty Private Set Intersection for Small Sets
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Published:2023-11-30
Issue:23
Volume:12
Page:4851
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ISSN:2079-9292
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Container-title:Electronics
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language:en
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Short-container-title:Electronics
Author:
Zhou Ji1, Liu Zhusen2, Wang Luyao1, Zhao Chuan3, Liu Zhe1, Zhou Lu1
Affiliation:
1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China 2. Research Center for Basic Theories of Intelligent Computing, Research Institute of Basic Theories, Zhejiang Lab, Hangzhou 311500, China 3. Quan Cheng Laboratory, Jinan 250103, China
Abstract
Private set intersection (PSI) is a pivotal subject in the realm of privacy computation. Numerous research endeavors have concentrated on situations involving vast and imbalanced sets. Nevertheless, there is a scarcity of existing PSI protocols tailored for small sets. Those that exist are either restricted to interactions between two parties or necessitate resource-intensive homomorphic operations. To bring forth practical multiparty private set intersection solutions for small sets, we present two multiparty PSI protocols founded on the principles of Oblivious Key–Value Stores (OKVSs), polynomials, and gabled cuckoo tables. Our security analysis underscores the resilience of these protocols against malicious models and collision attacks. Through experimental evaluations, we establish that, in comparison to related endeavors, our protocols excel in small-set contexts, particularly in low-bandwidth wide area network (WAN) settings.
Funder
National Key R&D Program of China National Natural Science Foundation of China Shenzhen Science and Technology Program Key R&D Program of Guangdong Province Natural Science Foundation of Jiangsu Province Shenzhen Virtual University Park Support Scheme China Postdoctoral Science Foundation
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference35 articles.
1. Keller, M., Orsini, E., and Scholl, P. (2016, January 24–28). MASCOT: Faster Malicious Arithmetic Secure Computation with Oblivious Transfer. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, Vienna, Austria. 2. Angel, S., Chen, H., Laine, K., and Setty, S. (2018, January 20–24). PIR with Compressed Queries and Amortized Query Processing. Proceedings of the 2018 IEEE Symposium on Security and Privacy (SP), San Francisco, CA, USA. 3. Kolesnikov, V., Kumaresan, R., Rosulek, M., and Trieu, N. (2016, January 24–28). Efficient Batched Oblivious PRF with Applications to Private Set Intersection. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, Vienna, Austria. 4. Kulshrestha, A., and Mayer, J. (2022, January 10–12). Estimating Incidental Collection in Foreign Intelligence Surveillance: Large-Scale Multiparty Private Set Intersection with Union and Sum. Proceedings of the 31st USENIX Security Symposium (USENIX Security 22), Boston, MA, USA. 5. Uzun, E., Chung, S.P., Kolesnikov, V., Boldyreva, A., and Lee, W. (2021, January 11–13). Fuzzy Labeled Private Set Intersection with Applications to Private Real-Time Biometric Search. Proceedings of the 30th USENIX Security Symposium (USENIX Security 21), USENIX Association, Virtually.
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