METHOD FOR CLASSIFYING DATA TO DETERMINE HIDDEN STATES OF SYSTEM WHILE PRESERVING PRIVACY

摘要

A method classifies data to determine hidden states of a system, by first randomly permuting the data and inserting client to generate private data. A server classifies the private data according to a hidden Markov model (HMM) to obtain permuted noisy estimates of the states and the chaff, which are returned to the client. The client then removes the chaff, inverts the permuted noisy estimates to obtain unpermuted noisy estimates of the states.