An Efficient 3-Party Framework for Privacy-Preserving Neural Network Inference
european symposium on research in computer security(2020)
摘要
In the era of big data, users pay more attention to data privacy issues in many application fields, such as healthcare, finance, and so on. However, in the current application scenarios of machine learning as a service, service providers require users’ private inputs to complete neural network inference tasks. Previous works have shown that some cryptographic tools can be used to achieve the secure neural network inference, but the performance gap is still existed to make those techniques practical.
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关键词
privacy-preserving
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