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Developing an Efficient Secure Query Processing Algorithm for Unstructured Data on Encrypted Databases

Research Authors
Mohamed A. Fouly, Taysir Hassan A. Soliman and Ahmed I. Taloba
Research Date
Research Department
Research File
Research Rank
2022 10th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)
Research Publisher
IEEE
Research Vol
12
Research Website
https://jac-ecc22.ejust.edu.eg/
Research Year
2022
Research_Pages
6
Research Abstract

A few years ago, information size increased unexpectedly and a data explosion happened. In this world of growing information, a change in database generation may also be required. Historically, we used a structured query language that works best with structured data. Now, we want to work with unstructured data as well as with structured data. The solution is to use not only SQL (NoSQL) database, this means not only structured query language. Recently, NoSQL databases are widely used in many organizations. Moreover, the data is kept in external services like Database as a Service (DaaS), where server-side and client-side security concerns are created. Additionally, the database's query processing by several clients using complicated techniques and a shared resource environment may lead to ineffective data processing and retrieval. An effective data processing technique among several customers can be used to retrieve data in a secure and effective manner. In this paper, we present an Efficient Secure Query Processing Algorithm for Unstructured Data (ESQPA_U) for efficient query processing by applying data compression techniques before transferring the encrypted results from the server to clients. We have solved security concerns by using CryptDB to encrypt a database on the server to protect the data. Encryption methods have recently been suggested to give customers secrecy in cloud storage. The queries can be processed using encrypted data using this technique without having to first decrypt it. In order to evaluate ESQPA_U performance, it is contrasted with CryptDB existing query processing method. According to results, storage space is more effective and can save up to 57% of its original space.