A SEMANTIC BASED POLICY MANAGEMENT FRAMEWORK FOR CLOUD COMPUTING ENVIRONMENTS

Cloud computing paradigm has gained tremendous momentum and generated intensive interest. Although security issues are delaying its fast adoption, cloud computing is an unstoppable force and we need to provide security mechanisms to ensure its secure adoption. In this dissertation, we mainly focus on issues related to policy management and access control in the cloud. Currently, users have to use diverse access control mechanisms to protect their data when stored on the cloud service providers (CSPs). Access control policies may be specified in different policy languages and heterogeneity of access policies pose significant problems.An ideal policy management system should be able to work with all data regardless of where they are stored. Semantic Web technologies when used for policy management, can help address the crucial issues of interoperability of heterogeneous CSPs. In this dissertation, we propose a semantic based policy management framework for cloud computing environments which consists of two main components, namely policy management and specification component and policy evolution component. In the policy management and specification component, we first introduce policy management as a service (PMaaS), a cloud based policy management framework that give cloud users a unified control point for specifying authorization policies, regardless of where the data is stored. Then, we present semantic based policy management framework which enables users to specify access control policies using semantic web technologies and helps address heterogeneity issues of cloud computing environments. We also model temporal constraints and restrictions in GTRBAC using OWL and show how ontologies can be used to specify temporal constraints. We present a proof of concept implementation of the proposed framework and provide some performance evaluation. In the policy evolution component, we propose to use role mining techniques to deal with policy evolution issues and present StateMiner, a heuristic algorithm to find an RBAC state as close as possible to both the deployed RBAC state and the optimal state. We also implement the proposed algorithm and perform some experiments to demonstrate its effectiveness

Use of Service Oriented Architecture for Scada Networks

Supervisory Control and Data Acquisition (SCADA) systems involve the use of distributed processing to operate geographically dispersed endpoint hardware components. They manage the control networks used to monitor and direct large-scale operations such as utilities and transit systems that are essential to national infrastructure. SCADA industrial control networks (ICNs) have long operated in obscurity and been kept isolated largely through strong physical security. Today, Internet technologies are increasingly being utilized to access control networks, giving rise to a growing concern that they are becoming more vulnerable to attack. Like SCADA, distributed processing is also central to cloud computing or, more formally, the Service Oriented Architecture (SOA) computing model. Certain distinctive properties differentiate ICNs from the enterprise networks that cloud computing developments have focused on. The objective of this project is to determine if modern cloud computing technologies can be also applied to improving dated SCADA distributed processing systems. Extensive research was performed regarding control network requirements as compared to those of general enterprise networks. Research was also conducted into the benefits, implementation, and performance of SOA to determine its merits for application to control networks. The conclusion developed is that some aspects of cloud computing might be usefully applied to SCADA systems but that SOA fails to meet ICN requirements in a certain essential areas. The lack of current standards for SOA security presents an unacceptable risk to SCADA systems that manage dangerous equipment or essential services. SOA network performance is also not sufficiently deterministic to suit many real-time hardware control applications. Finally, SOA environments cannot as yet address the regulatory compliance assurance requirements of critical infrastructure SCADA systems

A novel Hash-Based File Clustering scheme for efficient distributing, storing and retrieving of large scale Health Records

Cloud computing has been adopted as an efficient computing infrastructure model for provisioning resources and providing services to users. Several distributed resource models such as Hadoop and parallel databases have been deployed in healthcare-related services to manage electronic health records (EHR). However, these models are inefficient for managing a large number of small files and hence they are not widely deployed in Healthcare Information Systems. This paper proposed a novel Hash-Based File Clustering Scheme (HBFC) to distribute, store and retrieve EHR efficiently in cloud environments. The HBFC possesses two distinctive features: it utilizes hashing to distribute files into clusters in a control way and it utilizes P2P structures for data management. HBFC scheme is demonstrated to be effective in handling big health data that comprises of a large number of small files in various formats. It allows users to retrieve and access data records efficiently. The initial implementation results demonstrate that the proposed scheme outperforms original P2P system in term of data lookup latency

Cross-VM network attacks & their countermeasures within cloud computing environments

Cloud computing is a contemporary model in which the computing resources are dynamically scaled-up and scaled-down to customers, hosted within large-scale multi-tenant systems. These resources are delivered as improved, cost-effective and available upon request to customers. As one of the main trends of IT industry in modern ages, cloud computing has extended momentum and started to transform the mode enterprises build and offer IT solutions. The primary motivation in using cloud computing model is cost-effectiveness. These motivations can compel Information and Communication Technologies (ICT) organizations to shift their sensitive data and critical infrastructure on cloud environments. Because of the complex nature of underlying cloud infrastructure, the cloud environments are facing a large number of challenges of misconfigurations, cyber-attacks, root-kits, malware instances etc which manifest themselves as a serious threat to cloud environments. These threats noticeably decline the general trustworthiness, reliability and accessibility of the cloud. Security is the primary concern of a cloud service model. However, a number of significant challenges revealed that cloud environments are not as much secure as one would expect. There is also a limited understanding regarding the offering of secure services in a cloud model that can counter such challenges. This indicates the significance of the fact that what establishes the threat in cloud model. One of the main threats in a cloud model is of cost-effectiveness, normally cloud providers reduce cost by sharing infrastructure between multiple un-trusted VMs. This sharing has also led to several problems including co-location attacks. Cloud providers mitigate co-location attacks by introducing the concept of isolation. Due to this, a guest VM cannot interfere with its host machine, and with other guest VMs running on the same system. Such isolation is one of the prime foundations of cloud security for major public providers. However, such logical boundaries are not impenetrable. A myriad of previous studies have demonstrated how co-resident VMs could be vulnerable to attacks through shared file systems, cache side-channels, or through compromising of hypervisor layer using rootkits. Thus, the threat of cross-VM attacks is still possible because an attacker uses one VM to control or access other VMs on the same hypervisor. Hence, multiple methods are devised for strategic VM placement in order to exploit co-residency. Despite the clear potential for co-location attacks for abusing shared memory and disk, fine grained cross-VM network-channel attacks have not yet been demonstrated. Current network based attacks exploit existing vulnerabilities in networking technologies, such as ARP spoofing and DNS poisoning, which are difficult to use for VM-targeted attacks. The most commonly discussed network-based challenges focus on the fact that cloud providers place more layers of isolation between co-resided VMs than in non-virtualized settings because the attacker and victim are often assigned to separate segmentation of virtual networks. However, it has been demonstrated that this is not necessarily sufficient to prevent manipulation of a victim VM’s traffic. This thesis presents a comprehensive method and empirical analysis on the advancement of co-location attacks in which a malicious VM can negatively affect the security and privacy of other co-located VMs as it breaches the security perimeter of the cloud model. In such a scenario, it is imperative for a cloud provider to be able to appropriately secure access to the data such that it reaches to the appropriate destination. The primary contribution of the work presented in this thesis is to introduce two innovative attack models in leading cloud models, impersonation and privilege escalation, that successfully breach the security perimeter of cloud models and also propose countermeasures that block such types of attacks. The attack model revealed in this thesis, is a combination of impersonation and mirroring. This experimental setting can exploit the network channel of cloud model and successfully redirects the network traffic of other co-located VMs. The main contribution of this attack model is to find a gap in the contemporary network cloud architecture that an attacker can exploit. Prior research has also exploited the network channel using ARP poisoning, spoofing but all such attack schemes have been countered as modern cloud providers place more layers of security features than in preceding settings. Impersonation relies on the already existing regular network devices in order to mislead the security perimeter of the cloud model. The other contribution presented of this thesis is ‘privilege escalation’ attack in which a non-root user can escalate a privilege level by using RoP technique on the network channel and control the management domain through which attacker can manage to control the other co-located VMs which they are not authorized to do so. Finally, a countermeasure solution has been proposed by directly modifying the open source code of cloud model that can inhibit all such attacks

A Scalable Model for Secure Multiparty Authentication

Distributed system architectures such as cloud computing or the emergent architectures of the Internet Of Things, present significant challenges for security and privacy. Specifically, in a complex application there is a need to securely delegate access control mechanisms to one or more parties, who in turn can govern methods that enable multiple other parties to be authenticated in relation to the services that they wish to consume. We identify shortcomings in an existing proposal by Xu et al for multiparty authentication and evaluate a novel model from Al-Aqrabi et al that has been designed specifically for complex multiple security realm environments. The adoption of a Session Authority Cloud ensures that resources for authentication requests are scalable, whilst permitting the necessary architectural abstraction for myriad hardware IoT devices such as actuators and sensor networks, etc. In addition, the ability to ensure that session credentials are confirmed with the relevant resource principles means that the essential rigour for multiparty authentication is established

Resource Brokering in Grid Computing

Grid Computing has emerged in the academia and evolved towards the bases of what is currently known as Cloud Computing and Internet of Things (IoT). The vast collection of resources that provide the nature for Grid Computing environment is very complex; multiple administrative domains control access and set policies to the shared computing resources. It is a decentralized environment with geographically distributed computing and storage resources, where each computing resource can be modeled as an autonomous computing entity, yet collectively can work together. This is a class of Cooperative Distributed Systems (CDS). We extend this by applying characteristic of open environments to create a foundation for the next generation of computing platform where entities are free to join a computing environment to provide capabilities and take part as a collective in solving complex problems beyond the capability of a single entity. This thesis is focused on modeling “Computing” as a collective performance of individual autonomous fundamental computing elements interconnected in a “Grid” open environment structure. Each computing element is a node in the Grid. All nodes are interconnected through the “Grid” edges. Resource allocation is done at the edges of the “Grid” where the connected nodes are simply used to perform computation. The analysis put forward in this thesis identifies Grid Computing as a form of computing that occurs at the resource level. The proposed solution, coupled with advancements in technology and evolution of new computing paradigms, sets a new direction for grid computing research. The approach here is a leap forward with the well-defined set of requirements and specifications based on open issues with the focus on autonomy, adaptability and interdependency. The proposed approach examines current model for Grid Protocol Architecture and proposes an extension that addresses the open issues in the diverged set of solutions that have been created

Secure data sharing and processing in heterogeneous clouds

The extensive cloud adoption among the European Public Sector Players empowered them to own and operate a range of cloud infrastructures. These deployments vary both in the size and capabilities, as well as in the range of employed technologies and processes. The public sector, however, lacks the necessary technology to enable effective, interoperable and secure integration of a multitude of its computing clouds and services. In this work we focus on the federation of private clouds and the approaches that enable secure data sharing and processing among the collaborating infrastructures and services of public entities. We investigate the aspects of access control, data and security policy languages, as well as cryptographic approaches that enable fine-grained security and data processing in semi-trusted environments. We identify the main challenges and frame the future work that serve as an enabler of interoperability among heterogeneous infrastructures and services. Our goal is to enable both security and legal conformance as well as to facilitate transparency, privacy and effectivity of private cloud federations for the public sector needs. © 2015 The Authors

Cloud Security : A Review of Recent Threats and Solution Models

The most significant barrier to the wide adoption of cloud services has been attributed to perceived cloud insecurity (Smitha, Anna and Dan, 2012). In an attempt to review this subject, this paper will explore some of the major security threats to the cloud and the security models employed in tackling them. Access control violations, message integrity violations, data leakages, inability to guarantee complete data deletion, code injection, malwares and lack of expertise in cloud technology rank the major threats. The European Union invested €3m in City University London to research into the certification of Cloud security services. This and more recent developments are significant in addressing increasing public concerns regarding the confidentiality, integrity and privacy of data held in cloud environments. Some of the current cloud security models adopted in addressing cloud security threats were – Encryption of all data at storage and during transmission. The Cisco IronPort S-Series web security appliance was among security solutions to solve cloud access control issues. 2-factor Authentication with RSA SecurID and close monitoring appeared to be the most popular solutions to authentication and access control issues in the cloud. Database Active Monitoring, File Active Monitoring, URL Filters and Data Loss Prevention were solutions for detecting and preventing unauthorised data migration into and within clouds. There is yet no guarantee for a complete deletion of data by cloud providers on client requests however; FADE may be a solution (Yang et al., 2012)

Calm before the storm: the challenges of cloud computing in digital forensics

Cloud computing is a rapidly evolving information technology (IT) phenomenon. Rather than procure, deploy and manage a physical IT infrastructure to host their software applications, organizations are increasingly deploying their infrastructure into remote, virtualized environments, often hosted and managed by third parties. This development has significant implications for digital forensic investigators, equipment vendors, law enforcement, as well as corporate compliance and audit departments (among others). Much of digital forensic practice assumes careful control and management of IT assets (particularly data storage) during the conduct of an investigation. This paper summarises the key aspects of cloud computing and analyses how established digital forensic procedures will be invalidated in this new environment. Several new research challenges addressing this changing context are also identified and discussed