A PRIVACY ARCHITECTURE FOR DISTRIBUTED DATA MINING BASED ON ZERO-KNOWLEDGE COLLECTIONS OF DATABASES

摘要

A system and method for privacy-preserving distributed data mining are presented. The system comprises clients, servers, and a distributed database comprising databases each residing on a server, wherein original data in each database is changed into masked data using a masking function based on a query template generated by one or more clients, and in response to a query obtained from a client as an instantiation of the query template, the masked data is retrieved and the query result on the original data is obtained using a reconstruction function. The query result can be displayed on a computer. The query template and the query can be functions or protocols among clients. The retrieved masked data and the reconstruction function can compute an accurate query result on the original data without revealing additional information in the database having some original data that generates said query result.