
- •Cloud Computing
- •Foreword
- •Preface
- •Introduction
- •Expected Audience
- •Book Overview
- •Part 1: Cloud Base
- •Part 2: Cloud Seeding
- •Part 3: Cloud Breaks
- •Part 4: Cloud Feedback
- •Contents
- •1.1 Introduction
- •1.1.1 Cloud Services and Enabling Technologies
- •1.2 Virtualization Technology
- •1.2.1 Virtual Machines
- •1.2.2 Virtualization Platforms
- •1.2.3 Virtual Infrastructure Management
- •1.2.4 Cloud Infrastructure Manager
- •1.3 The MapReduce System
- •1.3.1 Hadoop MapReduce Overview
- •1.4 Web Services
- •1.4.1 RPC (Remote Procedure Call)
- •1.4.2 SOA (Service-Oriented Architecture)
- •1.4.3 REST (Representative State Transfer)
- •1.4.4 Mashup
- •1.4.5 Web Services in Practice
- •1.5 Conclusions
- •References
- •2.1 Introduction
- •2.2 Background and Related Work
- •2.3 Taxonomy of Cloud Computing
- •2.3.1 Cloud Architecture
- •2.3.1.1 Services and Modes of Cloud Computing
- •Software-as-a-Service (SaaS)
- •Platform-as-a-Service (PaaS)
- •Hardware-as-a-Service (HaaS)
- •Infrastructure-as-a-Service (IaaS)
- •2.3.2 Virtualization Management
- •2.3.3 Core Services
- •2.3.3.1 Discovery and Replication
- •2.3.3.2 Load Balancing
- •2.3.3.3 Resource Management
- •2.3.4 Data Governance
- •2.3.4.1 Interoperability
- •2.3.4.2 Data Migration
- •2.3.5 Management Services
- •2.3.5.1 Deployment and Configuration
- •2.3.5.2 Monitoring and Reporting
- •2.3.5.3 Service-Level Agreements (SLAs) Management
- •2.3.5.4 Metering and Billing
- •2.3.5.5 Provisioning
- •2.3.6 Security
- •2.3.6.1 Encryption/Decryption
- •2.3.6.2 Privacy and Federated Identity
- •2.3.6.3 Authorization and Authentication
- •2.3.7 Fault Tolerance
- •2.4 Classification and Comparison between Cloud Computing Ecosystems
- •2.5 Findings
- •2.5.2 Cloud Computing PaaS and SaaS Provider
- •2.5.3 Open Source Based Cloud Computing Services
- •2.6 Comments on Issues and Opportunities
- •2.7 Conclusions
- •References
- •3.1 Introduction
- •3.2 Scientific Workflows and e-Science
- •3.2.1 Scientific Workflows
- •3.2.2 Scientific Workflow Management Systems
- •3.2.3 Important Aspects of In Silico Experiments
- •3.3 A Taxonomy for Cloud Computing
- •3.3.1 Business Model
- •3.3.2 Privacy
- •3.3.3 Pricing
- •3.3.4 Architecture
- •3.3.5 Technology Infrastructure
- •3.3.6 Access
- •3.3.7 Standards
- •3.3.8 Orientation
- •3.5 Taxonomies for Cloud Computing
- •3.6 Conclusions and Final Remarks
- •References
- •4.1 Introduction
- •4.2 Cloud and Grid: A Comparison
- •4.2.1 A Retrospective View
- •4.2.2 Comparison from the Viewpoint of System
- •4.2.3 Comparison from the Viewpoint of Users
- •4.2.4 A Summary
- •4.3 Examining Cloud Computing from the CSCW Perspective
- •4.3.1 CSCW Findings
- •4.3.2 The Anatomy of Cloud Computing
- •4.3.2.1 Security and Privacy
- •4.3.2.2 Data and/or Vendor Lock-In
- •4.3.2.3 Service Availability/Reliability
- •4.4 Conclusions
- •References
- •5.1 Overview – Cloud Standards – What and Why?
- •5.2 Deep Dive: Interoperability Standards
- •5.2.1 Purpose, Expectations and Challenges
- •5.2.2 Initiatives – Focus, Sponsors and Status
- •5.2.3 Market Adoption
- •5.2.4 Gaps/Areas of Improvement
- •5.3 Deep Dive: Security Standards
- •5.3.1 Purpose, Expectations and Challenges
- •5.3.2 Initiatives – Focus, Sponsors and Status
- •5.3.3 Market Adoption
- •5.3.4 Gaps/Areas of Improvement
- •5.4 Deep Dive: Portability Standards
- •5.4.1 Purpose, Expectations and Challenges
- •5.4.2 Initiatives – Focus, Sponsors and Status
- •5.4.3 Market Adoption
- •5.4.4 Gaps/Areas of Improvement
- •5.5.1 Purpose, Expectations and Challenges
- •5.5.2 Initiatives – Focus, Sponsors and Status
- •5.5.3 Market Adoption
- •5.5.4 Gaps/Areas of Improvement
- •5.6 Deep Dive: Other Key Standards
- •5.6.1 Initiatives – Focus, Sponsors and Status
- •5.7 Closing Notes
- •References
- •6.1 Introduction and Motivation
- •6.2 Cloud@Home Overview
- •6.2.1 Issues, Challenges, and Open Problems
- •6.2.2 Basic Architecture
- •6.2.2.1 Software Environment
- •6.2.2.2 Software Infrastructure
- •6.2.2.3 Software Kernel
- •6.2.2.4 Firmware/Hardware
- •6.2.3 Application Scenarios
- •6.3 Cloud@Home Core Structure
- •6.3.1 Management Subsystem
- •6.3.2 Resource Subsystem
- •6.4 Conclusions
- •References
- •7.1 Introduction
- •7.2 MapReduce
- •7.3 P2P-MapReduce
- •7.3.1 Architecture
- •7.3.2 Implementation
- •7.3.2.1 Basic Mechanisms
- •Resource Discovery
- •Network Maintenance
- •Job Submission and Failure Recovery
- •7.3.2.2 State Diagram and Software Modules
- •7.3.3 Evaluation
- •7.4 Conclusions
- •References
- •8.1 Introduction
- •8.2 The Cloud Evolution
- •8.3 Improved Network Support for Cloud Computing
- •8.3.1 Why the Internet is Not Enough?
- •8.3.2 Transparent Optical Networks for Cloud Applications: The Dedicated Bandwidth Paradigm
- •8.4 Architecture and Implementation Details
- •8.4.1 Traffic Management and Control Plane Facilities
- •8.4.2 Service Plane and Interfaces
- •8.4.2.1 Providing Network Services to Cloud-Computing Infrastructures
- •8.4.2.2 The Cloud Operating System–Network Interface
- •8.5.1 The Prototype Details
- •8.5.1.1 The Underlying Network Infrastructure
- •8.5.1.2 The Prototype Cloud Network Control Logic and its Services
- •8.5.2 Performance Evaluation and Results Discussion
- •8.6 Related Work
- •8.7 Conclusions
- •References
- •9.1 Introduction
- •9.2 Overview of YML
- •9.3 Design and Implementation of YML-PC
- •9.3.1 Concept Stack of Cloud Platform
- •9.3.2 Design of YML-PC
- •9.3.3 Core Design and Implementation of YML-PC
- •9.4 Primary Experiments on YML-PC
- •9.4.1 YML-PC Can Be Scaled Up Very Easily
- •9.4.2 Data Persistence in YML-PC
- •9.4.3 Schedule Mechanism in YML-PC
- •9.5 Conclusion and Future Work
- •References
- •10.1 Introduction
- •10.2 Related Work
- •10.2.1 General View of Cloud Computing frameworks
- •10.2.2 Cloud Computing Middleware
- •10.3 Deploying Applications in the Cloud
- •10.3.1 Benchmarking the Cloud
- •10.3.2 The ProActive GCM Deployment
- •10.3.3 Technical Solutions for Deployment over Heterogeneous Infrastructures
- •10.3.3.1 Virtual Private Network (VPN)
- •10.3.3.2 Amazon Virtual Private Cloud (VPC)
- •10.3.3.3 Message Forwarding and Tunneling
- •10.3.4 Conclusion and Motivation for Mixing
- •10.4 Moving HPC Applications from Grids to Clouds
- •10.4.1 HPC on Heterogeneous Multi-Domain Platforms
- •10.4.2 The Hierarchical SPMD Concept and Multi-level Partitioning of Numerical Meshes
- •10.4.3 The GCM/ProActive-Based Lightweight Framework
- •10.4.4 Performance Evaluation
- •10.5 Dynamic Mixing of Clusters, Grids, and Clouds
- •10.5.1 The ProActive Resource Manager
- •10.5.2 Cloud Bursting: Managing Spike Demand
- •10.5.3 Cloud Seeding: Dealing with Heterogeneous Hardware and Private Data
- •10.6 Conclusion
- •References
- •11.1 Introduction
- •11.2 Background
- •11.2.1 ASKALON
- •11.2.2 Cloud Computing
- •11.3 Resource Management Architecture
- •11.3.1 Cloud Management
- •11.3.2 Image Catalog
- •11.3.3 Security
- •11.4 Evaluation
- •11.5 Related Work
- •11.6 Conclusions and Future Work
- •References
- •12.1 Introduction
- •12.2 Layered Peer-to-Peer Cloud Provisioning Architecture
- •12.4.1 Distributed Hash Tables
- •12.4.2 Designing Complex Services over DHTs
- •12.5 Cloud Peer Software Fabric: Design and Implementation
- •12.5.1 Overlay Construction
- •12.5.2 Multidimensional Query Indexing
- •12.5.3 Multidimensional Query Routing
- •12.6 Experiments and Evaluation
- •12.6.1 Cloud Peer Details
- •12.6.3 Test Application
- •12.6.4 Deployment of Test Services on Amazon EC2 Platform
- •12.7 Results and Discussions
- •12.8 Conclusions and Path Forward
- •References
- •13.1 Introduction
- •13.2 High-Throughput Science with the Nimrod Tools
- •13.2.1 The Nimrod Tool Family
- •13.2.2 Nimrod and the Grid
- •13.2.3 Scheduling in Nimrod
- •13.3 Extensions to Support Amazon’s Elastic Compute Cloud
- •13.3.1 The Nimrod Architecture
- •13.3.2 The EC2 Actuator
- •13.3.3 Additions to the Schedulers
- •13.4.1 Introduction and Background
- •13.4.2 Computational Requirements
- •13.4.3 The Experiment
- •13.4.4 Computational and Economic Results
- •13.4.5 Scientific Results
- •13.5 Conclusions
- •References
- •14.1 Using the Cloud
- •14.1.1 Overview
- •14.1.2 Background
- •14.1.3 Requirements and Obligations
- •14.1.3.1 Regional Laws
- •14.1.3.2 Industry Regulations
- •14.2 Cloud Compliance
- •14.2.1 Information Security Organization
- •14.2.2 Data Classification
- •14.2.2.1 Classifying Data and Systems
- •14.2.2.2 Specific Type of Data of Concern
- •14.2.2.3 Labeling
- •14.2.3 Access Control and Connectivity
- •14.2.3.1 Authentication and Authorization
- •14.2.3.2 Accounting and Auditing
- •14.2.3.3 Encrypting Data in Motion
- •14.2.3.4 Encrypting Data at Rest
- •14.2.4 Risk Assessments
- •14.2.4.1 Threat and Risk Assessments
- •14.2.4.2 Business Impact Assessments
- •14.2.4.3 Privacy Impact Assessments
- •14.2.5 Due Diligence and Provider Contract Requirements
- •14.2.5.1 ISO Certification
- •14.2.5.2 SAS 70 Type II
- •14.2.5.3 PCI PA DSS or Service Provider
- •14.2.5.4 Portability and Interoperability
- •14.2.5.5 Right to Audit
- •14.2.5.6 Service Level Agreements
- •14.2.6 Other Considerations
- •14.2.6.1 Disaster Recovery/Business Continuity
- •14.2.6.2 Governance Structure
- •14.2.6.3 Incident Response Plan
- •14.3 Conclusion
- •Bibliography
- •15.1.1 Location of Cloud Data and Applicable Laws
- •15.1.2 Data Concerns Within a European Context
- •15.1.3 Government Data
- •15.1.4 Trust
- •15.1.5 Interoperability and Standardization in Cloud Computing
- •15.1.6 Open Grid Forum’s (OGF) Production Grid Interoperability Working Group (PGI-WG) Charter
- •15.1.7.1 What will OCCI Provide?
- •15.1.7.2 Cloud Data Management Interface (CDMI)
- •15.1.7.3 How it Works
- •15.1.8 SDOs and their Involvement with Clouds
- •15.1.10 A Microsoft Cloud Interoperability Scenario
- •15.1.11 Opportunities for Public Authorities
- •15.1.12 Future Market Drivers and Challenges
- •15.1.13 Priorities Moving Forward
- •15.2 Conclusions
- •References
- •16.1 Introduction
- •16.2 Cloud Computing (‘The Cloud’)
- •16.3 Understanding Risks to Cloud Computing
- •16.3.1 Privacy Issues
- •16.3.2 Data Ownership and Content Disclosure Issues
- •16.3.3 Data Confidentiality
- •16.3.4 Data Location
- •16.3.5 Control Issues
- •16.3.6 Regulatory and Legislative Compliance
- •16.3.7 Forensic Evidence Issues
- •16.3.8 Auditing Issues
- •16.3.9 Business Continuity and Disaster Recovery Issues
- •16.3.10 Trust Issues
- •16.3.11 Security Policy Issues
- •16.3.12 Emerging Threats to Cloud Computing
- •16.4 Cloud Security Relationship Framework
- •16.4.1 Security Requirements in the Clouds
- •16.5 Conclusion
- •References
- •17.1 Introduction
- •17.1.1 What Is Security?
- •17.2 ISO 27002 Gap Analyses
- •17.2.1 Asset Management
- •17.2.2 Communications and Operations Management
- •17.2.4 Information Security Incident Management
- •17.2.5 Compliance
- •17.3 Security Recommendations
- •17.4 Case Studies
- •17.4.1 Private Cloud: Fortune 100 Company
- •17.4.2 Public Cloud: Amazon.com
- •17.5 Summary and Conclusion
- •References
- •18.1 Introduction
- •18.2 Decoupling Policy from Applications
- •18.2.1 Overlap of Concerns Between the PEP and PDP
- •18.2.2 Patterns for Binding PEPs to Services
- •18.2.3 Agents
- •18.2.4 Intermediaries
- •18.3 PEP Deployment Patterns in the Cloud
- •18.3.1 Software-as-a-Service Deployment
- •18.3.2 Platform-as-a-Service Deployment
- •18.3.3 Infrastructure-as-a-Service Deployment
- •18.3.4 Alternative Approaches to IaaS Policy Enforcement
- •18.3.5 Basic Web Application Security
- •18.3.6 VPN-Based Solutions
- •18.4 Challenges to Deploying PEPs in the Cloud
- •18.4.1 Performance Challenges in the Cloud
- •18.4.2 Strategies for Fault Tolerance
- •18.4.3 Strategies for Scalability
- •18.4.4 Clustering
- •18.4.5 Acceleration Strategies
- •18.4.5.1 Accelerating Message Processing
- •18.4.5.2 Acceleration of Cryptographic Operations
- •18.4.6 Transport Content Coding
- •18.4.7 Security Challenges in the Cloud
- •18.4.9 Binding PEPs and Applications
- •18.4.9.1 Intermediary Isolation
- •18.4.9.2 The Protected Application Stack
- •18.4.10 Authentication and Authorization
- •18.4.11 Clock Synchronization
- •18.4.12 Management Challenges in the Cloud
- •18.4.13 Audit, Logging, and Metrics
- •18.4.14 Repositories
- •18.4.15 Provisioning and Distribution
- •18.4.16 Policy Synchronization and Views
- •18.5 Conclusion
- •References
- •19.1 Introduction and Background
- •19.2 A Media Service Cloud for Traditional Broadcasting
- •19.2.1 Gridcast the PRISM Cloud 0.12
- •19.3 An On-demand Digital Media Cloud
- •19.4 PRISM Cloud Implementation
- •19.4.1 Cloud Resources
- •19.4.2 Cloud Service Deployment and Management
- •19.5 The PRISM Deployment
- •19.6 Summary
- •19.7 Content Note
- •References
- •20.1 Cloud Computing Reference Model
- •20.2 Cloud Economics
- •20.2.1 Economic Context
- •20.2.2 Economic Benefits
- •20.2.3 Economic Costs
- •20.2.5 The Economics of Green Clouds
- •20.3 Quality of Experience in the Cloud
- •20.4 Monetization Models in the Cloud
- •20.5 Charging in the Cloud
- •20.5.1 Existing Models of Charging
- •20.5.1.1 On-Demand IaaS Instances
- •20.5.1.2 Reserved IaaS Instances
- •20.5.1.3 PaaS Charging
- •20.5.1.4 Cloud Vendor Pricing Model
- •20.5.1.5 Interprovider Charging
- •20.6 Taxation in the Cloud
- •References
- •21.1 Introduction
- •21.2 Background
- •21.3 Experiment
- •21.3.1 Target Application: Value at Risk
- •21.3.2 Target Systems
- •21.3.2.1 Condor
- •21.3.2.2 Amazon EC2
- •21.3.2.3 Eucalyptus
- •21.3.3 Results
- •21.3.4 Job Completion
- •21.3.5 Cost
- •21.4 Conclusions and Future Work
- •References
- •Index

16 Security Issues to Cloud Computing |
275 |
Fig. 16.3 Cloud security relationship framework
The risks inherent in cloud computing are similar irrespective of the cloud model in use; however, there are unique security and information assurance requirements for each cloud deployment model. For example, security requirements for private clouds are different from that of a public cloud. Private clouds are perceived to be more secure than public clouds. Similarly, privacy concerns vary from private to public clouds.
To provide a realistic risk management to cloud computing, each cloud deployment model must be evaluated in its own right. In this respect, a cloud security relationship framework is proposed to provide this assessment (see Fig. 16.3). A cloud security relationship model is a theoretical framework to evaluate cloud deployment and delivery models based on security, cost and capability requirements.
16.3 Understanding Risks to Cloud Computing
A major concern with cloud computing is that the cloud provider offers the resources in the cloud, that is, the software, platform and infrastructure to the user (cloud consumer). In addition, user data/information also reside with the cloud
276 |
C. Onwubiko |
provider. The risk with this type of service is that user information could be abused, stolen, unlawfully distributed, compromised or harmed. There is no guarantee that user’s information/data could not be sold to its competitor. Unfortunately, this particular risk applies to all the three types of cloud delivery models, namely, SaaS, PaaS and IaaS.
Other risks to cloud computing also exist, and range from privacy, data protection, ownership, location and lack of reliable audit standard to data security procedure of most pioneer cloud providers, such as Google, Amazon, etc. According to Rick Gordon of Civitas Group, a concern with regard to cloud providers, especially Google Apps includes the lack of reliable security audit standard, data lock-in and Google’s opacity regarding its internal data security procedures [7].
In this section, risks to cloud computing are discussed with the view to outlining technical, administrative and ethical controls to provide guidance to cloud users.
16.3.1 Privacy Issues
Privacy even with traditional information security systems and networks is difficult to satisfy, and is a challenging issue to cloud computing. Cloud computing has significant implications for the privacy of personal information as well as maintaining the confidentiality of business and government information [6]. Concerns over privacy with current cloud computing offerings are apparent and real. For example, in a letter from Pam Dixon, executive director of the World Privacy Forum to the Los Angeles Mayor, Antonio Villaragosa, it was stated that, ‘our concern is that the transfer of so many City records to a cloud computing provider may threaten the privacy rights of City residents, undermine the security of other sensitive information, violate both state and federal laws, and potentially damage vital City legal and other interests [7]’. This concern is valid and true, especially with public clouds where sensitive individual and corporate information is put in the hands of thirdparty cloud providers, whose cloud infrastructure may not be regulated, and could traverse through geographical borders that impact both legal and regulatory requirements of the information being transported or stored.
Further, information in the cloud is perceived to have weaker privacy governance over that held in a personal physical computer system [6]. Hence, cloud users must be aware of the terms of contract they sign with a provider, and should be informed of the provider’s privacy and security guidelines and practices.
We recommend that privacy and security requirements of the different forms of cloud models are investigated and assessed, because not all cloud models raise the same privacy and confidentiality issues. As shown in Fig. 16.3, each cloud model offers unique security requirements, privacy capabilities and varying cost implications. For example, private or agency clouds are most suitable for protectively marked materials or classified information, but are more expensive to operate, while public clouds are suitable for personal non-confidential information such as sharing photos or pictures with friends.
16 Security Issues to Cloud Computing |
277 |
Again, it is important that cloud consumers (individual or corporate) assess the information requirements and understand the underlying regulatory and compliance requirements of their assets before migrating such assets to the cloud. Otherwise, they risk violating or undermining privacy, regulatory and compliance requirements of such assets.
Finally, users must apply due diligence on each cloud provider they intend to use, and must ensure that the necessary privacy laws are included in the service contract issued by the cloud provider.
16.3.2 Data Ownership and Content Disclosure Issues
Another issue to consider before migrating to the cloud includes ownership of information or data residing on the provider’s cloud. The moment a user puts data to the cloud, not only could the privacy of the data be lost, but also the ownership ‘authority’ over the data and right of disclosure could well be lost (by alienating ownership to the cloud provider). Although the lawful ownership and right of disclosure remains with the originating data owner, this could change quite quickly. Some providers retain the right of disclosure as data custodians, while others do not. This practice is gradually changing depending on the terms of the contract, which the provider issues to its customers.
There is a concern when the cloud provider becomes both the data owner and the data custodian. Even with traditional IT services, it is best practice to have separation of duties, where a different individual is the data owner, while another individual or group is the data custodian. This shifting paradigm with the cloud means that the cloud provider is both the data owner and data custodian for all data stored or transmitted from their cloud, including data from ‘delinquent organisations’, such as cybercriminals and organised crime groups. This practice violates the principle of separation of duties and job rotation; a fundamental principle of information security best practices.
We recommend that cloud users protectively mark their information and explicitly specify the ownership of information in the service contract. The service contract must be signed and indorsed by the cloud provider in form of a declaration. Protective marking is an administrative control used to classify information assets based on the degree of sensitivity afforded to that asset. For example, information can be protectively marked as ‘TOP SECRET’, ‘SECRET’, CONFIDENTIAL, etc.
16.3.3 Data Confidentiality
When a user puts information to a public cloud, what control does that user have over the data, its confidentiality, integrity or availability? When we consider small to medium-sized organisations or individual users, one could easily discuss the

278 |
C. Onwubiko |
risks associated with cloud computing services. What happens to the government, the enterprise in relation to the cloud? Can the cloud be used for government-protected marked information? For example, ‘SECRET’ document for defence agencies, such as for the CIA, MI5 or the MOD. I certainly do not think so, especially at this current stage of the cloud. These agencies have their own clouds, such as the MOD cloud, the DISA cloud, etc.; however, what is put in these clouds are still of great concern. It is pertinent to note that cloud computing is not ideal for all use cases. For example, protectively marked information asset up to the level of ‘SECRET’ or ‘TOP SECRET’ is not suitable for cloud computing (see Fig. 16.4). Similarly, ‘STRICTEST IN CONFIDENCE’ and ‘IN CONFIDENCE’ data may not be suitable for the cloud.
Fig. 16.4 Information classification to cloud mapping