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.
CITATION STYLE
Zaman, A., Siddique, M. A., Annisa, & Morimoto, Y. (2016). Secure computation of skyline query in MapTeduce. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10086 LNAI, pp. 345–360). Springer Verlag. https://doi.org/10.1007/978-3-319-49586-6_23
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