ENHANCING QUERY PERFORMANCE AND PRIVACY ON RELATIONAL CLOUD DATABASE (STATISTICS PROJECT TOPICS AND MATERIALS)
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.
1.1 Background of Study
Database outsourcing has become a current trend in the Information Technology Industry due to the enormous amount of digital content stored and generated on a daily basis by individuals and corporations. According to Liu and Ting (2010), enterprises are becoming data-centric and increasingly producing huge amounts of data daily. Most importantly, is the management of the data as it transits to and from the storage servers. Database as a service (DaaS) model provides users with Internet access, the power to create, store, modify and retrieve data from anywhere in the world. This technology primarily saves cost in terms of procuring hardware, software and manpower. It also ensures elastic scaling and availability. A key problem in outsourcing the storage and processing of data is that parts of the data may be sensitive, such as business secrets, credit card numbers, health records or other personal information (Kamara and Lauter, 2010).