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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EMIRIS: Eavesdropping on Iris Information via Electromagnetic Side Channel

Wenhao Li (Shandong University), Jiahao Wang (Shandong University), Guoming Zhang (Shandong University), Yanni Yang (Shandong University), Riccardo Spolaor (Shandong University), Xiuzhen Cheng (Shandong University), Pengfei Hu (Shandong University)

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Automatic Library Fuzzing through API Relation Evolvement

Jiayi Lin (The University of Hong Kong), Qingyu Zhang (The University of Hong Kong), Junzhe Li (The University of Hong Kong), Chenxin Sun (The University of Hong Kong), Hao Zhou (The Hong Kong Polytechnic University), Changhua Luo (The University of Hong Kong), Chenxiong Qian (The University of Hong Kong)

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YuraScanner: Leveraging LLMs for Task-driven Web App Scanning

Aleksei Stafeev (CISPA Helmholtz Center for Information Security), Tim Recktenwald (CISPA Helmholtz Center for Information Security), Gianluca De Stefano (CISPA Helmholtz Center for Information Security), Soheil Khodayari (CISPA Helmholtz Center for Information Security), Giancarlo Pellegrino (CISPA Helmholtz Center for Information Security)

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