Xiangfu Song (National University of Singapore), Dong Yin (Ant Group), Jianli Bai (The University of Auckland), Changyu Dong (Guangzhou University), Ee-Chien Chang (National University of Singapore)

A secret-shared shuffle (SSS) protocol permutes a secret-shared vector using a random secret permutation. It has found numerous applications, however, it is also an expensive operation and often a performance bottleneck. Chase et al. (Asiacrypt'20) recently proposed a highly efficient semi-honest two-party SSS protocol known as the CGP protocol. It utilizes purposely designed pseudorandom correlations that facilitate a communication-efficient online shuffle phase. That said, semi-honest security is insufficient in many real-world application scenarios since shuffle is usually used for highly sensitive applications. Considering this, recent works (CANS'21, NDSS'22) attempted to enhance the CGP protocol with malicious security over authenticated secret sharings. However, we find that these attempts are flawed, and malicious adversaries can still learn private information via malicious deviations. This is demonstrated with concrete attacks proposed in this paper. Then the question is how to fill the gap and design a maliciously secure CGP shuffle protocol. We answer this question by introducing a set of lightweight correlation checks and a leakage reduction mechanism. Then we apply our techniques with authenticated secret sharings to achieve malicious security. Notably, our protocol, while increasing security, is also efficient. In the two-party setting, experiment results show that our maliciously secure protocol introduces an acceptable overhead compared to its semi-honest version and is more efficient than the state-of-the-art maliciously secure SSS protocol from the MP-SPDZ library.

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Rui Zhu (Indiana University Bloominton), Di Tang (Indiana University Bloomington), Siyuan Tang (Indiana University Bloomington), Zihao Wang (Indiana University Bloomington), Guanhong Tao (Purdue University), Shiqing Ma (University of Massachusetts Amherst), XiaoFeng Wang (Indiana University Bloomington), Haixu Tang (Indiana University, Bloomington)

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Arjun Arunasalam (Purdue University), Habiba Farrukh (University of California, Irvine), Eliz Tekcan (Purdue University), Z. Berkay Celik (Purdue University)

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Takami Sato (University of California, Irvine), Yuki Hayakawa (Keio University), Ryo Suzuki (Keio University), Yohsuke Shiiki (Keio University), Kentaro Yoshioka (Keio University), Qi Alfred Chen (University of California, Irvine)

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Bernoulli Honeywords

Ke Coby Wang (Duke University), Michael K. Reiter (Duke University)

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