The follow-up to the acclaimed Organizations in the Computer Age this book, originally published in 1996, reveals that since computers had become increasingly linked in networks which span the world, information could be transmitted instantaneously to all parts of the organization. It describes the experiences of six organizations and draws lessons which apply very widely. The issues raised include: the impact on employment levels and organizational structure; the effects of network technology and organization structure and control; the extent of management choice; the role of change agents. This book shows that the introduction of computer networks raises new challenges concerning how the process of change is managed. The lessons from these cases could be widely applied in other organizations undertaking similar large-scale investments in new technology at the time.

This book focuses on the fundamental concepts of IP routing and distance-vector routing protocols (RIPv2 and EIGRP). It discusses routing protocols from a practicing engineer's perspective, linking theory and fundamental concepts to common practices and everyday examples. The book benefits and reflects the author's more than 22 years of designing and working with IP routing devices and protocols (and Telecoms systems, in general). Every aspect of the book is written to reflect current best practices using real-world examples. This book describes the various methods used by routers to learn routing information. The author includes discussion of the characteristics of the different dynamic routing protocols, and how they differ in design and operation. He explains the processing steps involved in forwarding IP packets through an IP router to their destination and discusses the various mechanisms IP routers use for controlling routing in networks. The discussion is presented in a simple style to make it comprehensible and appealing to undergraduate and graduate level students, research and practicing engineers, scientists, IT personnel, and network engineers. It is geared toward readers who want to understand the concepts and theory of IP routing protocols, through real-world example systems and networks. Focuses on the fundamental concepts of IP routing and distance-vector routing protocols (RIPv2 and EIGRP). Describes the various methods used by routers to learn routing information. Includes discussion of the characteristics of the different dynamic routing protocols, and how they differ in design and operation. Provides detailed descriptions of the most common distance-vector routing protocols RIPv2 and EIGRP. Discusses the various mechanisms IP routers use for controlling routing in networks. James Aweya, PhD, is a chief research scientist at the Etisalat British Telecom Innovation Center (EBTIC), Khalifa University, Abu Dhabi, UAE. He has authored four books including this book and is a senior member of the Institute of Electrical and Electronics Engineers (IEEE).

This book discusses link-state routing protocols (OSPF and IS-IS), and the path-vector routing protocol (BGP). It covers their most identifying characteristics, operations, and the databases they maintain. Material is presented from a practicing engineer's perspective, linking theory and fundamental concepts to common practices and real-world examples. Every aspect of the book is written to reflect current best practices using real-world examples. The book begins with a detailed description of the OSPF area types and hierarchical routing, and the different types of routers used in an OSPF autonomous system. The author goes on to describe in detail the different OSPF packet types, and inbound and outbound processing of OSPF link-state advertisements (LSAs). Next, the book gives an overview of the main features of IS-IS. The author then discusses the two-level routing hierarchy for controlling the distribution of intra-domain (Level 1) and inter-domain (Level 2) routing information within an IS-IS routing domain. He then describes in detail IS-IS network address formats, IS-IS routing metrics, IS-IS packet types, IS-IS network types and adjacency formation, IS-IS LSDB and synchronization, and IS-IS authentication. The book then reviews the main concepts of path-vector routing protocols, and describes BGP packet types, BGP session states and Finite State Machine, BGP path attributes types, and BGP Autonomous System Numbers (ASNs). Focuses solely on link-state routing protocols (OSPF and IS-IS), and the only path-vector routing protocol in use today (BGP). Reviews the basic concepts underlying the design of IS-IS and provides a detailed description of IS-IS area types and hierarchical routing, and the different types of routers used by IS-IS. Discusses the two-level routing hierarchy for controlling the distribution of intra-domain (Level 1) and inter-domain (Level 2) routing information within an IS-IS routing domain. Describes in detail BGP packet types, BGP session states and Finite State Machine, BGP path attributes types, and BGP ASNs, includes a high-level view of the typical BGP router and its components, and inbound and outbound message processing. James Aweya, PhD, is a chief research scientist at the Etisalat British Telecom Innovation Center (EBTIC), Khalifa University, Abu Dhabi, UAE. He has authored four books including this book and is a senior member of the Institute of Electrical and Electronics Engineers (IEEE).

A staggering 70% of digital transformations have failed as per McKinsey. The key reason why enterprises are failing in their digital transformation journey is because there is no standard framework existing in the industry that enterprises can use to transform themselves to digital. There are several books that speak about technologies such as Cloud, Artificial Intelligence and Data Analytics in silos, but none of these provides a holistic view on how enterprises can embark on a digital transformation journey and be successful using a combination of these technologies. FORMULA 4.0 is a methodology that provides clear guidance for enterprises aspiring to transform their traditional operating model to digital. Enterprises can use this framework as a readymade guide and plan their digital transformation journey. This book is intended for all chief executives, software managers, and leaders who intend to successfully lead this digital transformation journey. An enterprise can achieve success in digital transformation only of it can create an IT Platform that will enable them to adopt any new technology seamlessly into existing IT estate; deliver new products and services to the market in shorter durations; make business decisions with IT as an enabler and utilize automation in all its major business and IT processes. Achieving these goals is what defines a digital enterprise -- Formula 4.0 is a methodology for enterprises to achieve these goals and become digital. Essentially, there is no existing framework in the market that provides a step-by-step guide to enterprises on how to embark on their successful digital transformation journey. This book enables such transformations. Overall, the Formula 4.0 is an enterprise digital transformation framework that enables organizations to become truly digital.

Everyday technology is constantly changing, and it's hard to keep up with it at times. What is all this talk about automation, STEM, analytics and super-computers, and how will it really affect my daily life at work and in the home? This book is a simple guide to everyday technology and analytics written in plain language. It starts with explaining how computer networks are increasing in speed so fast that we can do more in less time than ever before. It explains the analytical jargon in plain English and why robotics in the home will be aided by the new technology of the quantum computer. Richly furnished with over 200 illustrations, photos and with minimal equations, A Simple Guide to Technology and Analytics is a ready reference book for those times when you don't really understand the technology and analytics being talked about. It explains complicated topics such as automated character recognition in a very simple way, and has simple exercises for the reader to fully understand the technology (with answers at the back). It even has explanations on how home appliances work, which are very useful the next time you go shopping for a microwave or TV. Even the Glossary at the back can be used as a quick look-up explanation for those on the go.

This book focuses on sustainability issues post COVID-19 outbreak, discusses ways to restrict global spread of the pandemic, and also how to survive holistically in the environment. It also discusses the economic impacts on the world due to the coronavirus outbreak. There is a strong need for monitoring and analysis of pandemics for sustainability like epidemic risk analysis by using pattern recognition or the mental health challenges during an outbreak. This book presents ways to find solutions and gives insights to explore innovative methods and predictive modeling techniques, such that masses are prevented from pandemics.

Coud reliability engineering is a leading issue of cloud services. Cloud service providers guarantee computation, storage and applications through service-level agreements (SLAs) for promised levels of performance and uptime. Cloud Reliability Engineering: Technologies and Tools presents case studies examining cloud services, their challenges, and the reliability mechanisms used by cloud service providers. These case studies provide readers with techniques to harness cloud reliability and availability requirements in their own endeavors. Both conceptual and applied, the book explains reliability theory and the best practices used by cloud service companies to provide high availability. It also examines load balancing, and cloud security. Written by researchers and practitioners, the book's chapters are a comprehensive study of cloud reliability and availability issues and solutions. Various reliability class distributions and their effects on cloud reliability are discussed. An important aspect of reliability block diagrams is used to categorize poor reliability of cloud infrastructures, where enhancement can be made to lower the failure rate of the system. This technique can be used in design and functional stages to determine poor reliability of a system and provide target improvements. Load balancing for reliability is examined as a migrating process or performed by using virtual machines. The approach employed to identify the lightly loaded destination node to which the processes/virtual machines migrate can be optimized by employing a genetic algorithm. To analyze security risk and reliability, a novel technique for minimizing the number of keys and the security system is presented. The book also provides an overview of testing methods for the cloud, and a case study discusses testing reliability, installability, and security. A comprehensive volume, Cloud Reliability Engineering: Technologies and Tools combines research, theory, and best practices used to engineer reliable cloud availability and performance.

This book vividly illustrates all the promising and potential machine learning (ML) and deep learning (DL) algorithms through a host of real-world and real-time business use cases. Machines and devices can be empowered to self-learn and exhibit intelligent behavior. Also, Big Data combined with real-time and runtime data can lead to personalized, prognostic, predictive, and prescriptive insights. This book examines the following topics: Cognitive machines and devices Cyber physical systems (CPS) The Internet of Things (IoT) and industrial use cases Industry 4.0 for smarter manufacturing Predictive and prescriptive insights for smarter systems Machine vision and intelligence Natural interfaces K-means clustering algorithm Support vector machine (SVM) algorithm A priori algorithms Linear and logistic regression Applied Learning Algorithms for Intelligent IoT clearly articulates ML and DL algorithms that can be used to unearth predictive and prescriptive insights out of Big Data. Transforming raw data into information and relevant knowledge is gaining prominence with the availability of data processing and mining, analytics algorithms, platforms, frameworks, and other accelerators discussed in the book. Now, with the emergence of machine learning algorithms, the field of data analytics is bound to reach new heights. This book will serve as a comprehensive guide for AI researchers, faculty members, and IT professionals. Every chapter will discuss one ML algorithm, its origin, challenges, and benefits, as well as a sample industry use case for explaining the algorithm in detail. The book's detailed and deeper dive into ML and DL algorithms using a practical use case can foster innovative research.

Many applications follow the distributed computing paradigm, in which parts of the application are executed on different network-interconnected computers. The extension of these applications in terms of number of users or size has led to an unprecedented increase in the scale of the infrastructure that supports them. Large-Scale Distributed Computing and Applications: Models and Trends offers a coherent and realistic image of today's research results in large scale distributed systems, explains state-of-the-art technological solutions for the main issues regarding large scale distributed systems, and presents the benefits of using large scale distributed systems and the development process of scientific and commercial distributed applications.

Fueled by ubiquitous computing ambitions, the edge is at the center of confluence of many emergent technological trends such as hardware-rooted trust and code integrity, 5G, data privacy and sovereignty, blockchains and distributed ledgers, ubiquitous sensors and drones, autonomous systems and real-time stream processing. Hardware and software pattern maturity have reached a tipping point so that scenarios like smart homes, smart factories, smart buildings, smart cities, smart grids, smart cars, smart highways are in reach of becoming a reality. While there is a great desire to bring born-in-the-cloud patterns and technologies such as zero-downtime software and hardware updates/upgrades to the edge, developers and operators alike face a unique set of challenges due to environmental differences such as resource constraints, network availability and heterogeneity of the environment. The first part of the book discusses various edge computing patterns which the authors have observed, and the reasons why these observations have led them to believe that there is a need for a new architectural paradigm for the new problem domain. Edge computing is examined from the app designer and architect's perspectives. When they design for edge computing, they need a new design language that can help them to express how capabilities are discovered, delivered and consumed, and how to leverage these capabilities regardless of location and network connectivity. Capability-Oriented Architecture is designed to provide a framework for all of these. This book is for everyone who is interested in understanding what ubiquitous and edge computing means, why it is growing in importance and its opportunities to you as a technologist or decision maker. The book covers the broad spectrum of edge environments, their challenges and how you can address them as a developer or an operator. The book concludes with an introduction to a new architectural paradigm called capability-based architecture, which takes into consideration the capabilities provided by an edge environment. .

Provides a structured look, at the unique characteristic for smart sensor networks to resolving the issues of many real-world applications in a broad range of areas such as Smart Healthcare, Engineering, Scientific Research, Social Media, Industrial Automation and more Offers a systematic look at the unique characteristics of AI based wireless sensor networks through their usage in a broad range of areas Delivers recent trends and core concepts in both analytics and application in smart sensor networks using AI Explores the development and application of AI and evolutionary computing as applied to wireless sensor networks Focuses on stepwise discussion, exhaustive literature review, detailed analysis and discussion, rigorous experimentation result and an application-oriented approach.

Make Software Architecture Choices That Maximize Value and Innovation "[Vernon and Jaskula] provide insights, tools, proven best practices, and architecture styles both from the business and engineering viewpoint. . . . This book deserves to become a must-read for practicing software engineers, executives as well as senior managers." --Michael Stal, Certified Senior Software Architect, Siemens Technology Strategic Monoliths and Microservices helps business decision-makers and technical team members clearly understand their strategic problems through collaboration and identify optimal architectural approaches, whether the approach is distributed microservices, well-modularized monoliths, or coarser-grained services partway between the two. Leading software architecture experts Vaughn Vernon and Tomasz Jaskula show how to make balanced architectural decisions based on need and purpose, rather than hype, so you can promote value and innovation, deliver more evolvable systems, and avoid costly mistakes. Using realistic examples, they show how to construct well-designed monoliths that are maintainable and extensible, and how to gradually redesign and reimplement even the most tangled legacy systems into truly effective microservices. Link software architecture planning to business innovation and digital transformation Overcome communication problems to promote experimentation and discovery-based innovation Master practices that support your value-generating goals and help you invest more strategically Compare architectural styles that can lead to versatile, adaptable applications and services Recognize when monoliths are your best option and how best to architect, design, and implement them Learn when to move monoliths to microservices and how to do it, whether they're modularized or a "Big Ball of Mud" Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Assisting organizations in improving their project management processes, the Project Management Maturity Model defines the industry standard for measuring project management maturity and agile and adaptive capabilities. Project Management Maturity Model, Fourth Edition provides a roadmap showing organizations how to move to higher levels of organizational behavior, improving project success and organizational performance. It's a comprehensive tool for enhancing project management practices, covering areas critical to organizational improvement, such as the project management office, management oversight, and professional development. It also provides methods for optimizing project management processes and suggestions for deploying the model as a strategic tool in improving business outcomes. New material in each chapter also outlines good practices for implementing adaptive an agile processes. The book also includes the Project Portfolio Management Maturity Model, which covers best practices for determining portfolio maturity, setting short-term priorities, implementing benefits realization management, improving portfolio management processes and tracking progress. The author, J. Kent Crawford, CEO of PM Solutions, describes the basics of project management maturity, including the benefits of assessing maturity, and presents a comprehensive framework for improving organization's processes. Chapters are based on the ten project management knowledge areas specified in the Project Management Institute's standard, the PMBOK (R) Guide. This edition provides new and revised materials based on the PMBOK (R) Guide including a fresh focus on agile and adaptive methods, benefits realization, and organizational change management. Organizations can use this book to: Determine the maturity of your organization's project management processes Gauge readiness for agile transformation Map out a logical path to improve your organization's processes Set priorities for short-term process improvement Track and visualize improvements in project management over time Learn to translate process maturity into business results After an objective assessment, an organization can set its goals for increasing the capability of its processes and develop a plan for reaching those goals. This book is ideal for anyone involved with improving the capability of an organization's project and portfolio management processes.

Teams working in a crisis are operating in a high turbulence environment. Blue Shark Teams thrive in a crisis. They swim through turbulence and glide to project success. This book reveals the concepts and practical insight on how to create and lead Blue Shark Teams. The Blue Shark Model of Leading High-Performance Teams is based on Daniel Goleman's emotional intelligence model and Bruce Tuckman's team-building model (forming, storming, norming, performing, and adjourning). This book shows how to apply these models to large companies, small-to-medium size businesses, and projects during a crisis. It explains how managers can develop their leadership style and lead high-performance teams. A real-life case study, which was a success story during the COVID-19 pandemic, is discussed to elaborate the team-building and emotional intelligence models. The lessons learned from this case study can be applied to any crisis in any industry across the spectrum, including healthcare, IT, telecom, construction, manufacturing, oil and gas, airlines, financial services, retail, public sector, and consulting. The book arms executives and managers with the concepts and techniques to lead and manage projects, teams, and companies during turbulent and volatile times. If you are a CEO, CIO, CTO, or CXO of a Fortune 500 company, a mid-to-small size Business Owner, a Project Manager, or a Senior Executive facing a crisis, then this book is for you. It describes real-life case studies and projects that shows how the theoretical frameworks and models developed by leading researchers can be applied successfully to companies and projects, especially during a crisis and pandemic such as COVID-19.

Data virtualization can help you accomplish your goals with more flexibility and agility. Learn what it is and how and why it should be used with "Data Virtualization for Business Intelligence Systems." In this book, expert author Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects. You ll learn the difference is between this new form of data integration and older forms, such as ETL and replication, and gain a clear understanding of how data virtualization really works. "Data Virtualization for Business Intelligence Systems "outlines the advantages and disadvantages of data virtualization and illustrates how data virtualization should be applied in data warehouse environments. You ll come away with a comprehensive understanding of how data virtualization will make data warehouse environments more flexible and how it make developing operational BI applications easier. Van der Lans also describes the relationship between data virtualization and related topics, such as master data management, governance, and information management, so you come away with a big-picture understanding as well as all the practical know-how you need to virtualize your data.
First independent book on data virtualization that explains in a product-independent way how data virtualization technology works. Illustrates concepts using examples developed with commercially available products. Shows you how to solve common data integration challenges such as data quality, system interference, and overall performance by following practical guidelines on using data virtualization. Apply data virtualization right away with three chapters full of practical implementation guidance. Understand the big picture of data virtualization and its relationship with data governance and information management. "

Today, it is not uncommon for practices and hospitals to be on their second or third EHR and/or contemplating a transition from the traditional on-premise model to a cloud-based system. As a follow-up to Complete Guide and Toolkit to Successful EHR Adoption ( (c)2011 HIMSS), this book builds on the best practices of the first edition, fast-forwarding to the latest innovations that are currently leveraged and adopted by providers and hospitals. We examine the role that artificial intelligence (AI) is now playing in and around EHR technology. We also address the advances in analytics and deep learning (also known as deep structured or hierarchical learning) and explain this topic in practical ways for even the most novice reader to comprehend and apply. The challenges of EHR to EHR migrations and data conversions will also be covered, including the use of the unethical practice of data blocking used as a tactic by some vendors to hold data hostage. Further, we explore innovations related to interoperability, cloud computing, cyber security, and electronic patient/consumer engagement. Finally, this book will deal with what to do with aging technology and databases, which is an issue rarely considered in any of the early publications on healthcare technology. What is the proper way to retire a legacy system, and what are the legal obligations of data archiving? Though a lot has changed since the 2011 edition, many of the fundamentals remain the same and will serve as a foundation for the next generation of EHR adopters and/or those moving on to their second, third, fourth, and beyond EHRs.

The book provides a complete and detailed description of the recent wireless technologies including Wi-Fi, Bluetooth, ZigBee and WiMAX. These technologies are considered to be important topics in the telecommunication industry in the next decade. Some critical subjects are particularly developed such as security, quality of service, roaming and power conservation. The book also includes some chapters on practical aspects.

VANET (vehicular ad hoc network) is a subgroup of MANET (mobile ad hoc network). It enables communication among vehicles on the road and between related infrastructures. This book addresses the basic elements of VANET along with components involved in the communication with their functionalities and configurations. It contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms, and protocols, and addresses the different services provided by VANET with the help of a scenario showing a network tackling an emergency. Features: * Covers all important concepts of VANET for beginners and different road scenarios in VANET * Covers essential communication protocols in VANET * Introduces approaches for VANET implementation using simulators * Provides a classification of messages and a priority-based message forwarding strategy This book is aimed at undergraduates, postgraduates, industry, researchers, and research scholars in information and communications technology.

The threat landscape is evolving with tremendous speed. We are facing an extremely fast-growing attack surface with a diversity of attack vectors, a clear asymmetry between attackers and defenders, billions of connected IoT devices, mostly reactive detection and mitigation approaches, and finally big data challenges. The clear asymmetry of attacks and the enormous amount of data are additional arguments to make it necessary to rethink cybersecurity approaches in terms of reducing the attack surface, to make the attack surface dynamic, to automate the detection, risk assessment, and mitigation, and to investigate the prediction and prevention of attacks with the utilization of emerging technologies like blockchain, artificial intelligence and machine learning. This book contains eleven chapters dealing with different Cybersecurity Issues in Emerging Technologies. The issues that are discussed and analyzed include smart connected cars, unmanned ships, 5G/6G connectivity, blockchain, agile incident response, hardware assisted security, ransomware attacks, hybrid threats and cyber skills gap. Both theoretical analysis and experimental evaluation of state-of-the-art techniques are presented and discussed. Prospective readers can be benefitted in understanding the future implications of novel technologies and proposed security solutions and techniques. Graduate and postgraduate students, research scholars, academics, cybersecurity professionals, and business leaders will find this book useful, which is planned to enlighten both beginners and experienced readers.

Issues surrounding business complexity plague organizations throughout the world. This situation is particularly true of the numerous complex projects and programs upon which organizations embark on a regular basis. Current project management processes and standards are based on Newtonian/Cartesian principles, such as linearity, reductionism, and single source problem causation. However, complex projects exhibit both Newtonian/Cartesian characteristics and complex systems characteristics, such as emergence, self-organization, non-linearity, non-reductionism, and multi-source problem causation. To conduct successful projects, complementary ways of approaching projects are required, and new competencies for those who manage projects and for those on project teams are required as well. There are a number of books available to help project managers and teams address the issue of systems behavior. However, there are none that approach complex projects from a neuroscience-based approach to human behavior and ambiguity. This book does exactly that in order to reduce project complexity and thereby increase the probability of project success. Cognitive Readiness in Project Teams looks to the concept of cognitive readiness (CR), first developed by the United States Department of Defense to better prepare and manage teams of individuals in complex battlefield situations. Its intent is to make project managers and teams more focused, responsive, resilient and adaptive through self-mastery and the mastering of interpersonal relationships. It introduces a CR framework for project managers and teams. This framework has neuroscience fundamentals and theorems as the foundation for the three pillars of CR: mindfulness, emotional intelligence, and social intelligence. The book is a compendium of chapters written by renowned authors in the fields of project management, neuroscience, mindfulness, and emotional and social intelligence.

The development of computer software for nonlinear control systems has provided many benefits for teaching, research, and the development of control systems design. MATLAB is considered the dominant software platforms for linear and nonlinear control systems analysis. This book provides an easy way to learn nonlinear control systems such as feedback linearization technique and Sliding mode control (Structure variable control) which are one of the most used techniques in nonlinear control dynamical systems; therefore teachers-students and researchers are all in need to handle such techniques; and since they are too difficult for them to handle such nonlinear controllers especially for a more complicated systems such as induction motor, satellite, and vehicles dynamical models. Thus, this document it is an excellent resource for learning the principle of feedback linearization and sliding mode techniques in an easy and simple way: Provides a briefs description of the feedback linearization and sliding mode control strategies Includes a simple method on how to determine the right and appropriate controller (P-PI-PID) for feedback linearization control strategy. A Symbolic MATLAB Based function for finding the feedback linearization and sliding mode controllers are developed and tested using several examples. A simple method for finding the approximate sliding mode controller parameters is introduced Where the program used to construct the nonlinear controller uses symbolic computations; such that the user should provide the program with the necessary functions f(x), g(x) and h(x) using the symbolic library.

A resource on quantitative methods and methodologies for researchers, practitioners, and doctoral students Demonstrates, in a step-by-step fashion, the development of the theoretically sound general framework allowing for instantiating a variety of research models. Illustrates a process of constructing of a variety of methodological modules- components comprised of complementary quantitative data analytic methods Explores the negative societal effects of implications of ICT and discusses future research directions to mitigate such effects

Examines the design and use of Intrusion Detection Systems (IDS) to secure Supervisory Control and Data Acquisition (SCADA) systems Cyber-attacks on SCADA systems the control system architecture that uses computers, networked data communications, and graphical user interfaces for high-level process supervisory management can lead to costly financial consequences or even result in loss of life. Minimizing potential risks and responding to malicious actions requires innovative approaches for monitoring SCADA systems and protecting them from targeted attacks. SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention is designed to help security and networking professionals develop and deploy accurate and effective Intrusion Detection Systems (IDS) for SCADA systems that leverage autonomous machine learning. Providing expert insights, practical advice, and up-to-date coverage of developments in SCADA security, this authoritative guide presents a new approach for efficient unsupervised IDS driven by SCADA-specific data. Organized into eight in-depth chapters, the text first discusses how traditional IT attacks can also be possible against SCADA, and describes essential SCADA concepts, systems, architectures, and main components. Following chapters introduce various SCADA security frameworks and approaches, including evaluating security with virtualization-based SCADAVT, using SDAD to extract proximity-based detection, finding a global and efficient anomaly threshold with GATUD, and more. This important book: Provides diverse perspectives on establishing an efficient IDS approach that can be implemented in SCADA systems Describes the relationship between main components and three generations of SCADA systems Explains the classification of a SCADA IDS based on its architecture and implementation Surveys the current literature in the field and suggests possible directions for future research SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention is a must-read for all SCADA security and networking researchers, engineers, system architects, developers, managers, lecturers, and other SCADA security industry practitioners.

Blockchain is a technology that has attracted the attention of all types of businesses. Cryptocurrency such as Bitcoin has gained the most attention, but now companies are applying Blockchain technology to develop solutions improving traditional applications and securing all types of transactions. Robust and innovative, this technology is being combined with other well-known technologies including Cloud Computing, Big Data, and IoT to revolutionize outcomes in all verticals. Unlike books focused on financial applications, Essential Enterprise Blockchain Concepts and Applications is for researchers and practitioners who are looking for secure, viable, low-cost, and workable applications to solve a broad range of business problems. The book presents research that rethinks how to incorporate Blockchain with existing technology. Chapters cover various applications based on Blockchain technology including: Digital voting Smart contracts Supply chain management Internet security Logistics management Identity management Securing medical devices Asset management Blockchain plays a significant role in providing security for data operations. It defines how trusted transactions can be carried out and addresses Internet vulnerability problems. Blockchain solves the security fault line between AI and IoT in smart systems as well as in other systems using devices connected to each other through public networks. Linear and permanent indexed records are maintained by Blockchain to face the vulnerability issues in a wide variety applications. In addition to applications, the book also covers consensus algorithms and protocols and performance of Blockchain algorithms.

This book brings together papers presented at the 3rd International Conference on Artificial Intelligence in China (ChinaAI), which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics covering all topics in Artificial Intelligence with new development in China, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD, DOE, etc).