Privacy-Preserving Deep Learning via Additively Homomorphic Encryption.
IEEE Transactions on Information Forensics and Security(2018)
摘要
We present a privacy-preserving deep learning system in which many learning participants perform neural network-based deep learning over a combined dataset of all, without revealing the participants' local data to a central server. To that end, we revisit the previous work by Shokri and Shmatikov (ACM CCS 2015) and show that, with their method, local data information may be leaked to an honest-but...
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关键词
Servers,Machine learning,Encryption,Neural networks,Privacy
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