NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
This paper studies the problem of privacy preserving inference where two parties, one of which is holding a model and the other holding a piece of text, would like to score the text by the model without exchanging neither the text or the model. The authors use secure multi party computation techniques to present a solution to this problem. The methods used in this work are not new. However, building a complete solution of the sort discussed here requires assembling together multiple pieces where for each piece there are multiple solutions to choose from. The authors to a good job at describing the pieces and the reasoning behind every choice they make such that the overall solution will perform well – I see that as a significant contribution. They also present a formal analysis of the security of the model and an empirical evaluation which makes this a well-rounded paper.