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.

View More Papers

MingledPie: A Cluster Mingling Approach for Mitigating Preference Profiling...

Cheng Zhang (Hunan University), Yang Xu (Hunan University), Jianghao Tan (Hunan University), Jiajie An (Hunan University), Wenqiang Jin (Hunan University)

Read More

Interventional Root Cause Analysis of Failures in Multi-Sensor Fusion...

Shuguang Wang (City University of Hong Kong), Qian Zhou (City University of Hong Kong), Kui Wu (University of Victoria), Jinghuai Deng (City University of Hong Kong), Dapeng Wu (City University of Hong Kong), Wei-Bin Lee (Information Security Center, Hon Hai Research Institute), Jianping Wang (City University of Hong Kong)

Read More

Query Privacy in Data Spaces

Shuwen Liu (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China), George C. Polyzos (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China and ExcID P.C., Athens, Greece)

Read More