Private Itemset Support Counting
Sven Laur, Helger Lipmaa and Taneli Mielikäinen
In: ICICS 2005, 10-13 Dec 2005,, Beijing, China.
Private itemset support counting (PISC) is a basic building block
of various privacy-preserving data mining algorithms. Briefly, in PISC, Client
wants to know the support of her itemset in Server’s database with the
usual privacy guarantees. First, we show that if the number of attributes is
small, then a communication-efficient PISC protocol can be constructed from a
communication-efficient oblivious transfer protocol. The converse is also true:
any communication-efficient PISC protocol gives rise to a communicationefficient
oblivious transfer protocol. Second, for the general case, we propose
a computationally efficient PISC protocol with linear communication in the size
of the database. Third, we show how to further reduce the communication by
using various tradeoffs and random sampling techniques.
Keywords: privacy-preserving data mining, private frequent itemset mining, private
itemset support counting, private subset inclusion test.