Pengzhi Xing (University of Electronic Science and Technology of China), Hongwei Li (University of Electronic Science and Technology of China), Meng Hao (Singapore Management University), Hanxiao Chen (University of Electronic Science and Technology of China), Jia Hu (University of Electronic Science and Technology of China), Dongxiao Liu (University of Electronic Science and Technology of China)

Function Secret Sharing (FSS) has emerged as a pivotal cryptographic tool for secure computation, delivering exceptional online efficiency with constant interaction rounds. However, the reliance on a trusted third party for key generation in existing FSS works compromises both security and practical deployment. In this paper, we introduce efficient distributed key generation schemes for FSS-based distributed point function and distributed comparison function, supporting both input and output to be arithmetic-shared. We further design crucial FSS-based components optimized for online efficiency, serving as the building blocks for advanced protocols. Finally, we propose an efficient framework for evaluating complex trigonometric functions, ubiquitous in scientific computations. Our framework leverages the periodic property of trigonometric functions, which reduces the bit length of input during FSS evaluation. This mitigates the potential performance bottleneck for FSS-based protocols incurred by bit length. Extensive empirical evaluations on real-world applications demonstrate a latency reduction of up to $14.73times$ and a communication cost decrease ranging from $27.67sim 184.42 times$ over the state-of-the-art work.

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Maxime Huyghe (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Clément Quinton (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Walter Rudametkin (Univ. Rennes, Inria, CNRS, UMR 6074 IRISA)

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Shangzhi Xu (The University of New South Wales), Jialiang Dong (The University of New South Wales), Weiting Cai (Delft University of Technology), Juanru Li (Feiyu Tech), Arash Shaghaghi (The University of New South Wales), Nan Sun (The University of New South Wales), Siqi Ma (The University of New South Wales)

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Dayong Ye (University of Technology Sydney), Tianqing Zhu (City University of Macau), Congcong Zhu (City University of Macau), Derui Wang (CSIRO’s Data61), Kun Gao (University of Technology Sydney), Zewei Shi (CSIRO’s Data61), Sheng Shen (Torrens University Australia), Wanlei Zhou (City University of Macau), Minhui Xue (CSIRO's Data61)

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Yonghao Zou (Beihang University and Peking University), Jia-Ju Bai (Beihang University), Zu-Ming Jiang (ETH Zurich), Ming Zhao (Arizona State University), Diyu Zhou (Peking University)

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