20 citations · 50 across the 14 of their papers we have counts for
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cs.CR2022★ 20 cited
SoK: Privacy Preserving Machine Learning using Functional Encryption: Opportunities and Challenges
Prajwal Panzade, Daniel Takabi
With the advent of functional encryption, new possibilities for computation on encrypted data have arisen. Functional Encryption enables data owners to grant third-party access to…
cs.CR2022★ 6 cited
SoK: Privacy-preserving Deep Learning with Homomorphic Encryption
Robert Podschwadt, Daniel Takabi, Peizhao Hu
Outsourced computation for neural networks allows users access to state of the art models without needing to invest in specialized hardware and know-how. The problem is that the us…