Name
Title | ||
|---|---|---|
Privacy-Preserving-Outsourced Association Rule Mining on Vertically Partitioned Databases. |
Abstract | ||
|---|---|---|
Association rule mining and frequent itemset mining are two popular and widely studied data analysis techniques for a range of applications. In this paper, we focus on privacy-preserving mining on vertically partitioned databases. In such a scenario, data owners wish to learn the association rules or frequent itemsets from a collective data set and disclose as little information about their (sensi... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TIFS.2016.2561241 | IEEE Transactions on Information Forensics and Security |
Keywords | Field | DocType |
Itemsets,Data privacy,Encryption,Business | Data mining,Data stream mining,Data analysis,Computer science,Server,Raw data,Encryption,Association rule learning,Information privacy,Database,Cloud computing | Journal |
Volume | Issue | ISSN |
11 | 8 | 1556-6013 |
Citations | PageRank | References |
26 | 0.85 | 21 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lichun Li | 1 | 41 | 2.53 |
| Rongxing Lu | 2 | 5091 | 301.87 |
| Kim-Kwang Raymond Choo | 3 | 4103 | 362.49 |
| Anwitaman Datta | 4 | 2183 | 130.88 |
| Jun Shao | 5 | 89 | 6.07 |