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

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.

The utilization of sensors, communications, and computer technologies to create greater efficiency in the generation, transmission, distribution, and consumption of electricity will enable better management of the electric power system. As the use of smart grid technologies grows, utilities will be able to automate meter reading and billing and consumers will be more aware of their energy usage and the associated costs. The results will require utilities and their suppliers to develop new business models, strategies, and processes. With an emphasis on reducing costs and improving return on investment (ROI) for utilities, Smart Grids: Clouds, Communications, Open Source, and Automation explores the design and implementation of smart grid technologies, considering the benefits to consumers as well as businesses. Focusing on industrial applications, the text: Provides a state-of-the-art account of the smart grid Explains how smart grid technologies are currently being used Includes detailed examples and test cases for real-life implementation Discusses trade-offs associated with the utilization of smart grid technologies Describes smart grid simulation software and offers insight into the future of the smart grid The electric power grid is in the early stages of a sea of change. Nobody knows which business models will survive, but companies heeding the lessons found in Smart Grids: Clouds, Communications, Open Source, and Automation might just increase their chances for success.

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.