ENHANCING QUERY PERFORMANCE AND PRIVACY ON RELATIONAL CLOUD DATABASE

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Date
2016-03
Authors
DZER, ROSEMARY MRUMUN
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Abstract
Database outsourcing has become a trend in the information technology industry because it offers scalability to the enormous amount of digital content stored and generated on a daily basis by individuals and corporations. In large outsourced databases the efficiency of data retrieval, especially as it relates to privacy, remains an open challenge, because traditional query languages cannot work with encrypted data. While several architectures, techniques and tools have been proffered to ensure that privacy and performance are balanced and optimized, each of these approaches has its limitations. This research proposed a framework which focused on enhancing query performance and privacy through the use of hash map and AES 128-bit encryption algorithm. The design and implementation of secureSQL is built on the client-side without any alteration to the DBMS structure. SecureSQL model guarantees efficiency and is able to execute 20 out of the 22 Transaction Processing Performance Council (TPC-H) benchmark queries while ensuring privacy. This is proof that it is not restricted to simple query constructs but is able to handle even complex queries involving nested sub queries and joins. The execution time of queries between the client and database on the cloud is reduced, as is evident in the comparative performance analysis between secureSQL and the traditional method of querying. Also, with increasing number of records, the proposed method maintains some degree of constancy in execution time thereby supporting the O(1) time complexity assertion for the use of the hash map data structure.
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A DISSERTATION SUBMITTED TO THE SCHOOL OF POSTGRADUATE STUDIES, AHMADU BELLO UNIVERSITY, ZARIA IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF A MASTER OF SCIENCE DEGREE IN COMPUTER SCIENCE DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE, AHMADU BELLO UNIVERSITY, ZARIA, NIGERIA
Keywords
QUERY PERFORMANCE, PRIVACY ON RELATIONAL, CLOUD DATABASE
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