Exploring the firewall security consistency in cloud computing during live migration

Virtualization technology adds great opportunities and challenges to the cloud computing paradigm. Resource management can be efficiently enhanced by employing Live Virtual Machine Migration (LVMM) techniques. Based on the literature of LVMM implementation in the virtualization environment, middle-boxes such as firewalls do not work effectively after LVMM as it introduces dynamic changes in network status and traffic, which may lead to critical security vulnerabilities. One key security hole is that the security context of the firewall do not move with the Virtual Machine after LVMM is triggered. This leads to inconsistency in the firewall level of protection of the migrated Virtual Machine. There is a lack in the literature of practical studies that address this problem in cloud computing platform. This paper demonstrates a practical analysis using OpenStack testbed to study the firewalls limitations in protecting virtual machines after LVMM. Two network scenarios are used to evaluate this problem. The results show that the security context problem does not exist in the stateless firewall but can exist in the stateful firewall

Infrastructure as a service: exploring network access control challenges

Cloud Computing Infrastructure as a Service (IaaS) is a great model for outsourcing IT infrastructure. It is built to offer fascinating features to support business development, such as elasticity, multi-tenancy, configurability and dynamicity. However, IaaS faces security challenges on account of its flexible nature. For this article, we studied the IaaS characteristics and investigated their related security challenges. We then elaborated these security challenges by exploring the security threats on live virtual machine migration as it is one of the main IaaS operations. We found that proper access control techniques and models are a critical element in enhancing IaaS and mitigating the identified security threats. Therefore, we investigated and contrasted the implemented and the proposed firewall architectures in IaaS as a firewall is a basic security appliance that enforces access control. We also explored and contrasted the proposed access control models in the IaaS. It was found that the traditional firewalls and access control models were not sufficient for IaaS. Therefore, there is a need to develop a proper access control model and enforcement techniques to mitigate IaaS security threats. Based on the security research trend and the results obtained in this articles exploration, we endorse an IaaS access control system built on a computational intelligent approach

IaaS-cloud security enhancement: an intelligent attribute-based access control model and implementation

The cloud computing paradigm introduces an efficient utilisation of huge computing resources by multiple users with minimal expense and deployment effort compared to traditional computing facilities. Although cloud computing has incredible benefits, some governments and enterprises remain hesitant to transfer their computing technology to the cloud as a consequence of the associated security challenges. Security is, therefore, a significant factor in cloud computing adoption. Cloud services consist of three layers: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). Cloud computing services are accessed through network connections and utilised by multi-users who can share the resources through virtualisation technology. Accordingly, an efficient access control system is crucial to prevent unauthorised access. This thesis mainly investigates the IaaS security enhancement from an access control point of view. [Continues.

Identity management in a public IaaS Cloud

In this thesis the unique environment that is the public IaaS cloud along with its differences from a traditional data center environment has been considered. The Cloud Security Alliance (CSA), states that “Managing identities and access control for enterprise applications remains one of the greatest challenges facing IT today”. The CSA also points out that “there is a lack of consistent secure methods for extending identity management into the cloud and across the cloud” [1]. This thesis examines this challenge of managing identities in the cloud by developing a list of best practices for implementing identity management in the cloud. These best practices were then tested by simulated misuse cases which were tested in a prototype of the implementation strategy. The results and analysis of the misuse cases show that the implementation of the identity management solution solves the problem of managing identities for the control of the infrastructure in the cloud. However, the analysis also shows that there are still areas where the properly implemented identity management solution fails to mitigate attacks to the infrastructure. These failures in particular are attacks that are sourced from the subscriber environments in the cloud. Finally, the best practices from this thesis also present some consistent methods for extending identity management into the cloud

Security Strategies to Prevent Data Breaches in Infrastructure as a Service Cloud Computing

Due to the ever-growing threat of security breaches that information technology (IT) organizations continually face, protecting customer information stored within the cloud is critical to ensuring data integrity. Research shows that new categories of data breaches constantly emerge; thus, security strategies that build trust in consumers and improve system performance are a must. The purpose of this qualitative multiple case study was to explore and analyze the strategies used by database administrators (DBAs) to secure data in a private infrastructure as a service (IaaS) cloud computing. The participants comprised of 6 DBAs from 2 IT companies in Baltimore, Maryland, with experience and knowledge of security strategies to secure data in private IaaS cloud computing. The disruptive innovation theory was the conceptual framework for this study. Data were collected using semistructured interviews and a review of 7 organizational documents. A thematic analysis was used to analyze the data. Four key themes emerged: importance of well-defined security measures in cloud computing, measures to address security controls in cloud computing, limitations of existing security controls in cloud computing, and future and potential security measures solutions in cloud computing. The findings may benefit DBAs and IT organizations by providing strategies to prevent future data breaches. Well-defined security strategies may protect an individual’s data, which in turn may promote individual well-being and build strong communities

Hybrid SDN Evolution: A Comprehensive Survey of the State-of-the-Art

Software-Defined Networking (SDN) is an evolutionary networking paradigm which has been adopted by large network and cloud providers, among which are Tech Giants. However, embracing a new and futuristic paradigm as an alternative to well-established and mature legacy networking paradigm requires a lot of time along with considerable financial resources and technical expertise. Consequently, many enterprises can not afford it. A compromise solution then is a hybrid networking environment (a.k.a. Hybrid SDN (hSDN)) in which SDN functionalities are leveraged while existing traditional network infrastructures are acknowledged. Recently, hSDN has been seen as a viable networking solution for a diverse range of businesses and organizations. Accordingly, the body of literature on hSDN research has improved remarkably. On this account, we present this paper as a comprehensive state-of-the-art survey which expands upon hSDN from many different perspectives

Building the Infrastructure for Cloud Security

Computer scienc

Medical Big Data Analysis in Hospital Information System

The rapidly increasing medical data generated from hospital information system (HIS) signifies the era of Big Data in the healthcare domain. These data hold great value to the workflow management, patient care and treatment, scientific research, and education in the healthcare industry. However, the complex, distributed, and highly interdisciplinary nature of medical data has underscored the limitations of traditional data analysis capabilities of data accessing, storage, processing, analyzing, distributing, and sharing. New and efficient technologies are becoming necessary to obtain the wealth of information and knowledge underlying medical Big Data. This chapter discusses medical Big Data analysis in HIS, including an introduction to the fundamental concepts, related platforms and technologies of medical Big Data processing, and advanced Big Data processing technologies

Virtual Machine Image Management for Elastic Resource Usage in Grid Computing

Grid Computing has evolved from an academic concept to a powerful paradigm in the area of high performance computing (HPC). Over the last few years, powerful Grid computing solutions were developed that allow the execution of computational tasks on distributed computing resources. Grid computing has recently attracted many commercial customers. To enable commercial customers to be able to execute sensitive data in the Grid, strong security mechanisms must be put in place to secure the customers' data. In contrast, the development of Cloud Computing, which entered the scene in 2006, was driven by industry: it was designed with respect to security from the beginning. Virtualization technology is used to separate the users e.g., by putting the different users of a system inside a virtual machine, which prevents them from accessing other users' data. The use of virtualization in the context of Grid computing has been examined early and was found to be a promising approach to counter the security threats that have appeared with commercial customers. One main part of the work presented in this thesis is the Image Creation Station (ICS), a component which allows users to administer their virtual execution environments (virtual machines) themselves and which is responsible for managing and distributing the virtual machines in the entire system. In contrast to Cloud computing, which was designed to allow even inexperienced users to execute their computational tasks in the Cloud easily, Grid computing is much more complex to use. The ICS makes it easier to use the Grid by overcoming traditional limitations like installing needed software on the compute nodes that users use to execute the computational tasks. This allows users to bring commercial software to the Grid for the first time, without the need for local administrators to install the software to computing nodes that are accessible by all users. Moreover, the administrative burden is shifted from the local Grid site's administrator to the users or experienced software providers that allow the provision of individually tailored virtual machines to each user. But the ICS is not only responsible for enabling users to manage their virtual machines themselves, it also ensures that the virtual machines are available on every site that is part of the distributed Grid system. A second aspect of the presented solution focuses on the elasticity of the system by automatically acquiring free external resources depending on the system's current workload. In contrast to existing systems, the presented approach allows the system's administrator to add or remove resource sets during runtime without needing to restart the entire system. Moreover, the presented solution allows users to not only use existing Grid resources but allows them to scale out to Cloud resources and use these resources on-demand. By ensuring that unused resources are shut down as soon as possible, the computational costs of a given task are minimized. In addition, the presented solution allows each user to specify which resources can be used to execute a particular job. This is useful when a job processes sensitive data e.g., that is not allowed to leave the company. To obtain a comparable function in today's systems, a user must submit her computational task to a particular resource set, losing the ability to automatically schedule if more than one set of resources can be used. In addition, the proposed solution prioritizes each set of resources by taking different metrics into account (e.g. the level of trust or computational costs) and tries to schedule the job to resources with the highest priority first. It is notable that the priority often mimics the physical distance from the resources to the user: a locally available Cluster usually has a higher priority due to the high level of trust and the computational costs, that are usually lower than the costs of using Cloud resources. Therefore, this scheduling strategy minimizes the costs of job execution by improving security at the same time since data is not necessarily transferred to remote resources and the probability of attacks by malicious external users is minimized. Bringing both components together results in a system that adapts automatically to the current workload by using external (e.g., Cloud) resources together with existing locally available resources or Grid sites and provides individually tailored virtual execution environments to the system's users