SecureBiNN: 3-party secure computation for binarized neural network inference

DOI10.1007/978-3-031-17143-7_14zbMath1524.68307OpenAlexW4296831808MaRDI QIDQ6109458

Xiang-Xue Li, Unnamed Author, Wen-Xing Zhu, Mengqi Wei

Publication date: 28 July 2023

Published in: Computer Security – ESORICS 2022 (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-031-17143-7_14

zbMATH Keywords

secure multi-party computationprivacy-preserving machine learningbinarized neural network

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Modes of computation (nondeterministic, parallel, interactive, probabilistic, etc.) (68Q10) Cryptography (94A60) Authentication, digital signatures and secret sharing (94A62) Computer security (68M25) Privacy of data (68P27)

Cites Work

• Unnamed Item
• Fast homomorphic evaluation of deep discretized neural networks
• Communication-efficient (client-aided) secure two-party protocols and its application
• Homomorphic encryption for arithmetic of approximate numbers
• Universally Composable Security
• High-Throughput Secure Three-Party Computation for Malicious Adversaries and an Honest Majority

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