Data Access Control in the Cloud Computing Environment for Bioinformatics

1. Introduction

Cloud computing facilitates fast and efficient parallel processing of terabyte-scale data in the virtual environment (Huthand & Chebula, 2011). In cloud computing, there are three entities (stakeholders) namely Data Owner (DO), Cloud Service Provider (CSP) and user. The DOs share their own data or file on the cloud server. The CSP provides the cloud services for both DO and user. The users access data or file from the cloud server (Namasudra et al., 2014; Zhang et al., 2010; Namasudra & Roy, 2017a). The users cannot access data randomly by their wishes. Each CSP has its own access policy or right. So, when the users want to access any data or file from the cloud server, they must satisfy the access right to access the requested data from the cloud environment.

There are mainly four types of cloud deployment models:

• 1.

  Private cloud

• 2.

  Public cloud

• 3.

  Community cloud

• 4.

  Hybrid cloud

A private cloud infrastructure is solely operated by a single organization. It can be managed by an organization or by a third party. In a public cloud, the CSP provides the resources, such as network, server, etc. to the users. Anyone can join in the public cloud. In a community cloud infrastructure, a cloud environment is shared by a community/several communities. All these communities must have a common goal. Hybrid cloud is the combination of public, private and community cloud. It is managed by a central administrator.

Cloud services can be provided in three ways, namely Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). Figure 1 shows the simple scenario of a cloud environment.

Figure 1.

Simple scenario of a cloud environment

In a cloud environment, when the CSP receives a data access request from a user, it must provide public key of the DO to the user to get the secret key and other necessary credentials. So, if the CSP takes much time to search the DO, the user must wait to get the details. Thus, in result, the data accessing time is also increased, and the user must need to pay more for using the cloud services. In the existing Access Control Model (ACM), the DO must be always online during the entire data communication process, so load on the CSP i.e. system overhead is increased (Gao et al., 2012). Another critical issue in a cloud environment is data security due to the presence of hackers. Those hackers are geographically distributed, and always want to unauthorized access of the confidential data. Sometimes, they change the original data, which is very difficult to identify for any cloud service provider. Many researchers have proposed many access control models to solve these issues, namely high searching time of the DO, high data or file accessing, high system overhead and data security (Namasudra, 2019; Sarkar et al., 2015; Namasudra et al., 2017a; Zhao et al., 2019; Namasudra et al., 2020a; Namasudra, 2018a; Namasudra et al., 2017b; Alguliyev et al., 2020; Namasudra et al., 2017c; Namasudra & Roy, 2016; Namasudra et al., 2020b; Namasudra & Deka, 2018a; Li et al., 2019; Namasudra et al., 2018a; Namasudra et al., 2020c; Namasudra & Deka, 2018b; Namasudra & Roy, 2018; Namasudra et al., 2018b; Deka & Borah, 2012; Namasudra & Roy, 2017b Namasudra et al., 2020d; Chakraborty et al., 2020; Namasudra et al., 2020e; Devi et al., 2020).

Bioinformatics is an interdisciplinary field that applies computational technique to analyze a large collection of biological data. Bioinformatics is the application of computer science to solve the problems of biological science. Enhancing the reproducibility of bioinformatics experiments requires robust computational environment for providing secure access of large-scale distributed biomedical data across the heterogeneous platforms in the cloud computing environment.