Journal
PROCEEDINGS OF THE VLDB ENDOWMENT
Volume 5, Issue 11, Pages 1340-1351Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.14778/2350229.2350251
Keywords
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Funding
- Air Force Office of Scientific Research MURI [FA9550-08-1-0265]
- National Science Foundation [1116991]
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [1116991] Funding Source: National Science Foundation
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The discovery of frequent itemsets can serve valuable economic and research purposes. Releasing discovered frequent itemsets, however, presents privacy challenges. In this paper, we study the problem of how to perform frequent item-set mining on transaction databases while satisfying differential privacy. We propose an approach, called PrivBasis, which leverages a novel notion called basis sets. A theta-basis set has the property that any itemset with frequency higher than. is a subset of some basis. We introduce algorithms for privately constructing a basis set and then using it to find the most frequent itemsets. Experiments show that our approach greatly outperforms the current state of the art.
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