Privacy-Enhanced Machine Learning with Functional Encryption

Tilen Marc, Miha Stopar, Jan Hartman, Manca Bizjak, Jolanda Modic
2019 Zenodo  
Functional ENcryption is a generalization of public-key encryption in which possessing a secret functional key allows one to learn a function of what the ciphertext is encrypting. This paper introduces the first fully-fledged open source cryptographic libraries for functional encryption. It also presents how Functional ENcryption can be used to build efficient privacy-enhanced machine learning models and it provides an implementation of three prediction services that can be applied on the
more » ... ted data. Finally, the paper discusses the advantages and disadvantages of the alternative approach for building privacy-enhanced machine learning models by using homomorphic encryption.
doi:10.5281/zenodo.3551691 fatcat:bta45eskejdnlc3btbieo26hka