Name
Abstract | ||
|---|---|---|
To select representative objects from a large scale database is an important step to understand the database. A skyline query, which retrieves a set of non-dominated objects, is one of popular methods for selecting representative objects. In this paper, we have considered a distributed algorithm for computing a skyline query in order to handle “big data”. In conventional distributed algorithms for computing a skyline query, the values of each object of a local database have to be disclosed to another. Recently, we have to be aware of privacy in a database, in which such disclosures of privacy information in conventional distributed algorithms are not allowed. In this work, we propose a novel approach to compute the skyline in a multi-parties computing environment without disclosing individual values of objects to another party. Our method is designed to work in MapReduce framework − in Hadoop framework. Our experimental results confirm the effectiveness and scalability of the proposed secure skyline computation. |
Year | Venue | Field |
|---|---|---|
2016 | ADMA | Skyline,Data mining,Secure multi-party computation,Computer science,Information security,Distributed algorithm,Skyline computation,Big data,Scalability |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
17 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Asif Zaman | 1 | 6 | 5.16 |
| Md. Anisuzzaman Siddique | 2 | 30 | 8.47 |
| annisa | 3 | 4 | 2.77 |
| Yasuhiko Morimoto | 4 | 528 | 341.88 |