Maliciously Secure Circuit Private Set Intersection via SPDZ-Compatible Oblivious PRF

Circuit Private Set Intersection (Circuit-PSI) allows two parties to compute a function f on items in the intersection of their input sets without revealing items in the intersection set. It is a well-known variant of PSI and has numerous practical applications. However, existing Circuit-PSI protocols only provide security against semi-honest adversaries. A straightforward approach to constructing a maliciously secure Circuit-PSI is to extend a pure garbled-circuit-based PSI (NDSS'12) to a maliciously secure circuit-PSI, but it will not be concretely efficient. Another is converting state-of-the-art semi-honest Circuit-PSI protocols (EUROCRYPT'21; PoPETS'22) to be secure in the malicious setting. However, it will come across the consistency issue (EUROCRYPT'11) since parties can not guarantee the inputs of the function f stay unchanged as obtained from the last step. This paper tackles the previously mentioned issue by presenting the first maliciously secure Circuit-PSI protocol. Our key innovation, the Distributed Dual-key Oblivious Pseudorandom Function (DDOPRF), enables the oblivious evaluation of secret-shared inputs using dual keys within the SPDZ MPC framework. Notably, this construction seamlessly ensures fairness within the Circuit-PSI. Compared to the state-of-the-art semi-honest Circuit-PSI protocol (PoPETS'22), experimental results demonstrate that our malicious Circuit-PSI protocol not only reduces around 5x communication costs but also enhances efficiency, particularly for modest input sets (<= 2^{14}) in the case of the WAN setting with high latency and limited bandwidth.

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Publication Details

Journal
Proceedings on Privacy Enhancing Technologies
Published
2025-03-07
DOI
https://doi.org/10.56553/popets-2025-0082
Citations
3
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
7.44

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article

Maliciously Secure Circuit Private Set Intersection via SPDZ-Compatible Oblivious PRF

Xiangfu Song, Jianying Zhou, Changyu Dong, Xiaojian Liang et al.
3 citations
Proceedings on Privacy Enhancing Technologies
Cryptography and Data Security
7.44
article

Maliciously Secure Circuit Private Set Intersection via SPDZ-Compatible Oblivious PRF

Xiangfu Song, Jianying Zhou, Changyu Dong, Xiaojian Liang, Ye Dong, Hong‐Yu Ren, Longbin Huang, Yaxi Yang
article en
3 citations

Abstract

Circuit Private Set Intersection (Circuit-PSI) allows two parties to compute a function f on items in the intersection of their input sets without revealing items in the intersection set. It is a well-known variant of PSI and has numerous practical applications. However, existing Circuit-PSI protocols only provide security against semi-honest adversaries. A straightforward approach to constructing a maliciously secure Circuit-PSI is to extend a pure garbled-circuit-based PSI (NDSS'12) to a maliciously secure circuit-PSI, but it will not be concretely efficient. Another is converting state-of-the-art semi-honest Circuit-PSI protocols (EUROCRYPT'21; PoPETS'22) to be secure in the malicious setting. However, it will come across the consistency issue (EUROCRYPT'11) since parties can not guarantee the inputs of the function f stay unchanged as obtained from the last step. This paper tackles the previously mentioned issue by presenting the first maliciously secure Circuit-PSI protocol. Our key innovation, the Distributed Dual-key Oblivious Pseudorandom Function (DDOPRF), enables the oblivious evaluation of secret-shared inputs using dual keys within the SPDZ MPC framework. Notably, this construction seamlessly ensures fairness within the Circuit-PSI. Compared to the state-of-the-art semi-honest Circuit-PSI protocol (PoPETS'22), experimental results demonstrate that our malicious Circuit-PSI protocol not only reduces around 5x communication costs but also enhances efficiency, particularly for modest input sets (<= 2^{14}) in the case of the WAN setting with high latency and limited bandwidth.

Proceedings on Privacy Enhancing TechnologiesVol. 2025(2)
Singapore University of Technology and Design (SG), National University of Singapore (SG), Guangzhou University (CN), ANT Foundation Italy Onlus (IT)
National Research Foundation, National Research Foundation Singapore, National Natural Science Foundation of China
Openalex Percentile: Top 4%
Cryptography and Data Security
7.44
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