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Top1. Introduction
The fast developments in Information and Communication Technology (ICT) have enabled the emerging of the “cloud” as a successful paradigm for conveniently storing, accessing, processing, and sharing information (Varghese & Buyya 2017). With its significant benefits of scalability and elasticity, the cloud paradigm has appealed companies as well as individuals, which are more and more resorting to the multitude of available providers for storing and processing data. Unfortunately, such convenience comes at the price of owners’ loss of control over their data, and consequent security threats, which can limit the potential widespread adoption and acceptance of the cloud computing paradigm (Singh et al., 2017). Figure 1 shows the different types of attacks for cloud services such as software, platform, application and infrastructure.
Figure 1. Different types of attacks for cloud services
On the one hand, cloud providers can be assumed to employ basic security mechanisms for protecting data in storage, processing, and communication, devoting resources to ensure security that many individuals and companies may not be able to afford. On the other hand, data owners, as well as users of the cloud, lose control over data and their processing. Currently, cloud services are provisioned and scheduled according to resources’ availability without ensuring the required security (Singh et al., 2017). The cloud provider should evolve its ecosystem to meet security requirements of each cloud component (Pietro et al., 2016) and specifically, deploy mechanisms to ensure the secure and autonomic management of resources.
In this research paper, we have proposed a conceptual model for security-aware allocation of cloud resources called STARK, which provides protection against security threats during resource management for workload execution. This work (STARK) is an extension of our previous research work i.e. STAR (Singh et al., 2017). The rest of paper is structured as follows. Section 2 presents proposed security-aware resource management model. Thereafter, we present a set of future research directions and conclude the paper in Section 3.
Top2. Stark: Security Based Resource Allocation Model For Clustered Workloads
As the scale of mobile networks and the population of mobile users increases, the applications of cloud computing have emerged where social users can use their mobile devices to exchange and share contents with each other (Qu et al., 2010). The security resource is needed to protect mobile social big data during the delivery. However, due to the limited security resource, how to allocate the security resource becomes a new challenge. Existing security-based resource management techniques only focuses on homogenous cloud workloads and provide protection against Denial of Service (DoS) attack (Wailly et al., 2012; Singh & Chana 2013; Bittencourt et al., 2017). To solve this problem, there is the need for a new solution, which can protect the cloud against different types of security attacks during the autonomic execution of cloud workloads.