Data Centric Security In Software Defined Networks Sdn

The book focuses on applying the data-centric security (DCS) concept and leveraging the unique capabilities of software-defined networks (SDN) to improve the security and resilience of corporate and government information systems used to process critical information and implement business processes requiring special protection. As organisations increasingly rely on information technology, cyber threats to data and infrastructure can significantly affect their operations and adversely impact critical business processes. Appropriate authentication, authorisation, monitoring, and response measures must be implemented within the perimeter of the system to protect against adversaries. However, sophisticated attackers can compromise the perimeter defences and even remain in the system for a prolonged time without the owner being aware of these facts. Therefore, new security paradigms such as Zero Trust and DCS aim to provide defence under the assumption that the boundary protections will be breached. Based on experience and lessons learned from research on the application of DCS to defence systems, the authors present an approach to integrating the DCS concept with SDN. They introduce a risk-aware approach to routing in SDN, enabling defence-in-depth and enhanced security for data in transit. The book describes possible paths for an organisation to transition towards DCS, indicating some open and challenging issues requiring further investigation. To allow interested readers to conduct detailed studies and evaluate the exemplary implementation of DCS over SDN, the text includes a short tutorial on using the emulation environment and links to the websites from which the software can be downloaded.

Security and Resilience in Intelligent Data-Centric Systems and Communication Networks presents current, state-of-the-art work on novel research in theoretical and practical resilience and security aspects of intelligent data-centric critical systems and networks. The book analyzes concepts and technologies that are successfully used in the implementation of intelligent data-centric critical systems and communication networks, also touching on future developments. In addition, readers will find in-demand information for domain experts and developers who want to understand and realize the aspects (opportunities and challenges) of using emerging technologies for designing and developing more secure and resilient intelligent data-centric critical systems and communication networks. Topics covered include airports, seaports, rail transport systems, plants for the provision of water and energy, and business transactional systems. The book is well suited for researchers and PhD interested in the use of security and resilient computing technologies. Includes tools and techniques to prevent and avoid both accidental and malicious behaviors Explains the state-of-the-art technological solutions for main issues hindering the development of monitoring and reaction solutions Describes new methods and technologies, advanced prototypes, systems, tools and techniques of future direction

This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).

User-Centric Networks (UCN) and Information-Centric Networks (ICN) are new communication paradigms to increase the efficiency of content delivery and also content availability. In this new concept, the network infrastructure actively contributes to content caching and distribution. This book presents the basic concepts of UCN and ICN, describes the main architecture proposals for these networks, and discusses the main challenges to their development. The book also looks at the current challenges for this concept, including naming, routing and caching on the network-core elements, several aspects of content security, user privacy, and practical issues in implementing UCN and ICN.

This book describes the concept of a Software Defined Mobile Network (SDMN), which will impact the network architecture of current LTE (3GPP) networks. SDN will also open up new opportunities for traffic, resource and mobility management, as well as impose new challenges on network security. Therefore, the book addresses the main affected areas such as traffic, resource and mobility management, virtualized traffics transportation, network management, network security and techno economic concepts. Moreover, a complete introduction to SDN and SDMN concepts. Furthermore, the reader will be introduced to cutting-edge knowledge in areas such as network virtualization, as well as SDN concepts relevant to next generation mobile networks. Finally, by the end of the book the reader will be familiar with the feasibility and opportunities of SDMN concepts, and will be able to evaluate the limits of performance and scalability of these new technologies while applying them to mobile broadb and networks.

Discusses virtual network security concepts Considers proactive security using moving target defense Reviews attack representation models based on attack graphs and attack trees Examines service function chaining in virtual networks with security considerations Recognizes machine learning and AI in network security

This edited book provides an optimal portrayal of the principles and applications related to network security. The book is thematically divided into five segments: Part A describes the introductory issues related to network security with some concepts of cutting-edge technologies; Part B builds from there and exposes the readers to the digital, cloud and IoT forensics; Part C presents readers with blockchain and cryptography techniques; Part D deals with the role of AI and machine learning in the context of network security. And lastly, Part E is written on different security networking methodologies. This is a great book on network security, which has lucid and well-planned chapters. All the latest security technologies are thoroughly explained with upcoming research issues. Details on Internet architecture, security needs, encryption, cryptography along with the usages of machine learning and artificial intelligence for network security are presented in a single cover. The broad-ranging text/reference comprehensively surveys network security concepts, methods, and practices and covers network security policies and goals in an integrated manner. It is an essential security resource for practitioners in networks and professionals who develop and maintain secure computer networks.