Secure and efficient multi-tenant database management system for cloud computing environment

Abstract

Multi-tenancy is one of the important feature of cloud computing environment. Multi-tenant database system in SaaS (Software as a Service) deployed in cloud infrastructure has gained wide interest in both academics as well as industries, as it provides scalability and economic benefit for both cloud service provider and end users. However, low trust on the rented computational resources prevents users from utilizing the same. Further, in multitenant systems the communication channels and other computational resources are shared, inducing privacy and security issues. As tenants are anonymous in nature, a user may not find a trustworthy co-tenant and tenants depend on cloud service provider to assign trustworthy co-tenants. However, cloud service provider allows maximum co-tenancy irrespective of the behaviors of tenants to maximize resource utilization. Of late, a number of approaches have been presented based on reputation management mechanism to identify good and malicious tenants. However, state-of-art models are not efficient when behavior of malicious tenant changes rapidly. In order to overcome the said research challenge, this work presents a secure and efficient multi-tenant database management system (SEMTDBMS) for cloud computing environment. SEMTDBMS first analyzes security requirement of tenant workers and suggests a secureness weight metric for selection of tenant worker. Subsequently, a novel workload scheduler for scheduling workload among tenants has been presented. Experiments are conducted considering OLTP benchmark such as TPC-C and Yahoo! Cloud Serving Benchmark (YCSB) benchmark with and without security compliances. SEMTDBMS show significant performance improvement in terms of latency and throughput over state-of-art model.