This book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.

This practical and didactic text/reference discusses the leading edge of secure cloud computing, exploring the essential concepts and principles, tools, techniques and deployment models in this field. Enlightening perspectives are presented by an international collection of pre-eminent authorities in cloud security assurance from both academia and industry.

Topics and features:

·         Describes the important general concepts and principles of security assurance in cloud-based environments

·         Presents applications and approaches to cloud security that illustrate the current state of the art

·         Reviews pertinent issues in relation to challenges that prevent organizations moving to cloud architectures

·         Provides relevant theoretical frameworks and the latest empirical research findings

·         Discusses real-world vulnerabilities of cloud-based software in order to address the challenges of securing distributed software

·         Highlights the practicalities of cloud security, and how applications can assure and comply with legislation

·         Includes review questions at the end of each chapter

This Guide to Security Assurance for Cloud Computing will be of great benefit to a broad audience covering enterprise architects, business analysts and leaders, IT infrastructure managers, cloud security engineers and consultants, and application developers involved in system design and implementation. The work is also suitable as a textbook for university instructors, with the outline for a possible course structure suggested in the preface.

The editors are all members of the Computing and Mathematics Department at the University of Derby, UK, where Dr. Shao Ying Zhu serves as a Senior Lecturer in Computing, Dr. Richard Hill as a Professor and Head of the Computing and Mathematics Department, and Dr. Marcello Trovati as a Senior Lecturer in Mathematics. The other publications of the editors include the Springer titles Big-Data Analytics and Cloud Computing, Guide to Cloud Computing and Cloud Computing for Enterprise Architectures.

This book highlights the importance of security in the design, development and deployment of systems based on Software-Defined Networking (SDN) and Network Functions Virtualization (NFV), together referred to as SDNFV. Presenting a comprehensive guide to the application of security mechanisms in the context of SDNFV, the content spans fundamental theory, practical solutions, and potential applications in future networks.

This book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.

This practical and didactic text/reference discusses the leading edge of secure cloud computing, exploring the essential concepts and principles, tools, techniques and deployment models in this field. Enlightening perspectives are presented by an international collection of pre-eminent authorities in cloud security assurance from both academia and industry.

Topics and features:

·         Describes the important general concepts and principles of security assurance in cloud-based environments

·         Presents applications and approaches to cloud security that illustrate the current state of the art

·         Reviews pertinent issues in relation to challenges that prevent organizations moving to cloud architectures

·         Provides relevant theoretical frameworks and the latest empirical research findings

·         Discusses real-world vulnerabilities of cloud-based software in order to address the challenges of securing distributed software

·         Highlights the practicalities of cloud security, and how applications can assure and comply with legislation

·         Includes review questions at the end of each chapter

This Guide to Security Assurance for Cloud Computing will be of great benefit to a broad audience covering enterprise architects, business analysts and leaders, IT infrastructure managers, cloud security engineers and consultants, and application developers involved in system design and implementation. The work is also suitable as a textbook for university instructors, with the outline for a possible course structure suggested in the preface.

The editors are all members of the Computing and Mathematics Department at the University of Derby, UK, where Dr. Shao Ying Zhu serves as a Senior Lecturer in Computing, Dr. Richard Hill as a Professor and Head of the Computing and Mathematics Department, and Dr. Marcello Trovati as a Senior Lecturer in Mathematics. The other publications of the editors include the Springer titles Big-Data Analytics and Cloud Computing, Guide to Cloud Computing and Cloud Computing for Enterprise Architectures.

This book highlights the importance of security in the design, development and deployment of systems based on Software-Defined Networking (SDN) and Network Functions Virtualization (NFV), together referred to as SDNFV. Presenting a comprehensive guide to the application of security mechanisms in the context of SDNFV, the content spans fundamental theory, practical solutions, and potential applications in future networks.