Authors: Yasuhiko Morimoto; Mohammad Shamsul Arefin; Mohammad Anisuzzaman Siddique
Addresses: Graduate School of Engineering, Hiroshima University, 1-7-1 Kagamiyama, Higashi-Hiroshima City 739-8521, Japan. ' Graduate School of Engineering, Hiroshima University, 1-7-1 Kagamiyama, Higashi-Hiroshima City 739-8521, Japan. ' Department of Computer Science and Engineering, University of Rajshahi, Rajshahi-6205, Bangladesh
Abstract: Given a set of objects, a skyline query finds the objects that are not dominated by another object. A skyline query helps us to filter unnecessary information efficiently and gives us clues for various decision making tasks. On the other hand, we usually have to hide individual record's values even though there is no ID information in the table in privacy aware environments. In such situation, we cannot use conventional skyline queries. To handle the privacy problem, we considered a skyline query for sets of objects in a database. In which we do not disclose individual record's values. Let s be the number of objects in each set and n be the number of objects in the database. There are nCs sets in the database. We consider an efficient algorithm for computing convex skyline of the nCs sets, which we call 'convex skyline sets'. We further expand the idea of 'convex skyline sets' to use in a cloud computing environment in this paper. We propose a method for computing a skyline set query from distributed databases without disclosing individual records to others. There is no doubt that most of the cloud service providers do not want to disclose any individual record in their database. The proposed method utilises an agent computing framework and solves the privacy problems of skyline queries in cloud computing environments.
Keywords: skyline queries; anonymity; privacy; agent computing; agent-based systems; distributed databases; cloud computing; information filtering; information retrieval.
International Journal of Computational Science and Engineering, 2012 Vol.7 No.1, pp.73 - 81
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 30 Mar 2012 *