Data Management over Garbled Bloom Filter for Private Set Intersection

Abstract

Increasing dependency of data availability and the fear of losing the private information during com- munication motivate the need of privacy protection. One of the common problems occurs when two par- ties need to privately compute the intersection of their respective sets of data. One or both parties must obtain the intersection (if one exists), while neither should learn anything about the other party set. Till date, one of the e cient approach has been presented with consideration of Big Data by Dong, Chen and Wen (CCS 2013). They have introduced a new data structure named as Garbled Bloom Filter (GBF), an improved Bloom lter, for the computa- tion of the Private Set Intersection (PSI). While the PSI protocol (DCW13 protocol) by Dong, Chen and Wen is pretty e cient, it does not support for managing dynamic data. In this paper, we present data management techniques on the server side of the DCW13 protocol, which compliment the DCW13 protocol.