Multi-join query optimization in bucket-based encrypted databases using an enhanced ant colony optimization algorithm

One of the organizations’ main concerns is to protect sensitive data in database systems, especially the ones outsourced to untrusted service providers. An effective solution for this issue is to employ database encryption methods. Among different encryption approaches, Bucket-based method has the advantage of balancing security and performance of database operations. However, generating false-positive results in executing queries is the main drawback of this method. On the other hand, multi-join queries are one of the most critical operations executed on these stored sensitive data. Hence, acceptable processing and response time in executing multi-join queries is required. In this paper, we propose an enhanced ant-colony algorithm (named BACO) which aims to reduce the required processing efforts in multi-join query optimization problem alongside with reducing the total false-positive results generated in Bucket-based encrypted databases. Our enhanced solution approach leads to much less response time without losing solutions’ quality. Experimental results denote that our proposed solution can yield 75% decrease in multi-join queries processing efforts and 74% decrease in the total amount of false-positive results in a faster manner and with better performance than previous methods.