Privacy Preserving Data Integration And Mining : Human Verification Of Matches

Suppose a match m has been found. Now humans at both or one of the sources S and T must examine m to verify its correctness. The goal is then to make certain such verification is privacy-preserving. The goal is to give humans enough information to verify matches, while preserving privacy. One way to achieve this can be randomly selecting some values for particular attributes and show the user only these values. It can be argued that revealing only few attribute values does not reveal anything useful about the distribution. Since two attributes are found to be similar, it can be argued that few samples does not reveal too much useful information.