Machine learning boosts the capabilities of security solutions in the modern cyber environment. However, there are also security concerns associated with machine learning models and approaches: the vulnerability of machine learning models to adversarial attacks is a fatal flaw in the artificial intelligence technologies, and the privacy of the data used in the training and testing periods is also causing increasing concern among users. This book reviews the latest research in the area, including effective applications of machine learning methods in cybersecurity solutions and the urgent security risks related to the machine learning models. The book is divided into three parts: Cyber Security Based on Machine Learning; Security in Machine Learning Methods and Systems; and Security and Privacy in Outsourced Machine Learning. Addressing hot topics in cybersecurity and written by leading researchers in the field, the book features self-contained chapters to allow readers to select topics that are relevant to their needs. It is a valuable resource for all those interested in cybersecurity and robust machine learning, including graduate students and academic and industrial researchers, wanting to gain insights into cutting-edge research topics, as well as related tools and inspiring innovations.

This comprehensive text/reference examines the various challenges to secure, efficient and cost-effective next-generation wireless networking. Topics and features: presents the latest advances, standards and technical challenges in a broad range of emerging wireless technologies; discusses cooperative and mesh networks, delay tolerant networks, and other next-generation networks such as LTE; examines real-world applications of vehicular communications, broadband wireless technologies, RFID technology, and energy-efficient wireless communications; introduces developments towards the 'Internet of Things' from both a communications and a service perspective; discusses the machine-to-machine communication model, important applications of wireless technologies in healthcare, and security issues in state-of-the-art networks.

This book constitutes the refereed post-conference proceedings of the 4th International Conference on Intelligence Science, ICIS 2020, held in Durgapur, India, in February 2021 (originally November 2020). The 23 full papers and 4 short papers presented were carefully reviewed and selected from 42 submissions. One extended abstract is also included. They deal with key issues in brain cognition; uncertain theory; machine learning; data intelligence; language cognition; vision cognition; perceptual intelligence; intelligent robot; and medical artificial intelligence.

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 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 explores fundamental scientific problems essential for autonomous cyber defense. Specific areas include: Game and control theory-based moving target defenses (MTDs) and adaptive cyber defenses (ACDs) for fully autonomous cyber operations; The extent to which autonomous cyber systems can be designed and operated in a framework that is significantly different from the human-based systems we now operate; On-line learning algorithms, including deep recurrent networks and reinforcement learning, for the kinds of situation awareness and decisions that autonomous cyber systems will require; Human understanding and control of highly distributed autonomous cyber defenses; Quantitative performance metrics for the above so that autonomous cyber defensive agents can reason about the situation and appropriate responses as well as allowing humans to assess and improve the autonomous system. This book establishes scientific foundations for adaptive autonomous cyber systems and ultimately brings about a more secure and reliable Internet. The recent advances in adaptive cyber defense (ACD) have developed a range of new ACD techniques and methodologies for reasoning in an adaptive environment. Autonomy in physical and cyber systems promises to revolutionize cyber operations. The ability of autonomous systems to execute at scales, scopes, and tempos exceeding those of humans and human-controlled systems will introduce entirely new types of cyber defense strategies and tactics, especially in highly contested physical and cyber environments. The development and automation of cyber strategies that are responsive to autonomous adversaries pose basic new technical challenges for cyber-security. This book targets cyber-security professionals and researchers (industry, governments, and military). Advanced-level students in computer science and information systems will also find this book useful as a secondary textbook.

This book provides the state-of-the-art development on security and privacy for fog/edge computing, together with their system architectural support and applications. This book is organized into five parts with a total of 15 chapters. Each area corresponds to an important snapshot. The first part of this book presents an overview of fog/edge computing, focusing on its relationship with cloud technology and the future with the use of 5G communication. Several applications of edge computing are discussed. The second part of this book considers several security issues in fog/edge computing, including the secure storage and search services, collaborative intrusion detection method on IoT-fog computing, and the feasibility of deploying Byzantine agreement protocols in untrusted environments. The third part of this book studies the privacy issues in fog/edge computing. It first investigates the unique privacy challenges in fog/edge computing, and then discusses a privacy-preserving framework for the edge-based video analysis, a popular machine learning application on fog/edge. This book also covers the security architectural design of fog/edge computing, including a comprehensive overview of vulnerabilities in fog/edge computing within multiple architectural levels, the security and intelligent management, the implementation of network-function-virtualization-enabled multicasting in part four. It explains how to use the blockchain to realize security services. The last part of this book surveys applications of fog/edge computing, including the fog/edge computing in Industrial IoT, edge-based augmented reality, data streaming in fog/edge computing, and the blockchain-based application for edge-IoT. This book is designed for academics, researchers and government officials, working in the field of fog/edge computing and cloud computing. Practitioners, and business organizations (e.g., executives, system designers, and marketing professionals), who conduct teaching, research, decision making, and designing fog/edge technology will also benefit from this book The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, and information systems, but also applies to students in business, education, and economics, who would benefit from the information, models, and case studies therein.

The topics addressed in this book are crucial for both the academic community and industry, since the vehicular network has become an essential building block for intelligent transportation systems. The systematic principle of this book provides valuable guidance on the deployment and implementation of V2X-enabled road-safety applications. In addition, this book carries out structured technologies from the MAC layer to the link and network layer, which can provide a general introduction for interested readers with a comprehensive understanding of applying vehicular networks in enhancing road safety, and offers a systematized view for researchers and practitioners in the field of vehicular networks to help them optimize and improve the desired vehicular communication systems. Road safety has always been the first priority for daily commuters on the road. Vehicular networks can be an effective solution to enhance road safety, via which vehicles can exchange cooperative awareness messages rapidly, contributing to better situation awareness and maneuvering cooperation. However, with the fast-changing network topology, intermittent wireless link, and dynamic traffic density, it is challenging to achieve satisfying network performance. This book introduces the background of vehicular networks, provides a comprehensive overview of networking techniques in supporting road-safety applications, states the technical motivations per the MAC, link, and network layer, and proposes/designs vehicular networking technologies at the corresponding layer respectively to guarantee low-latency and reliable V2X communications for road-safety applications. By extending the proposed networking technologies to support all types of vehicular services, this book also outlines open issues and research directions in future 5G and beyond vehicular networks.

As an important future network architecture, virtual network architecture has received extensive attention. Virtual network embedding (VNE) is one of the core services of network virtualization (NV). It provides solutions for various network applications from the perspective of virtual network resource allocation. The Internet aims to provide global users with comprehensive coverage. The network function requests of hundreds of millions of end users have brought great pressure to the underlying network architecture. VNE algorithm can provide effective support for the reasonable and efficient allocation of network resources, so as to alleviate the pressure off the Internet. At present, a distinctive feature of the Internet environment is that the quality of service (QoS) requirements of users are differentiated. Different regions, different times, and different users have different network function requirements. Therefore, network resources need to be reasonably allocated according to users' QoS requirements to avoid the waste of network resources. In this book, based on the analysis of the principle of VNE algorithm, we provide a VNE scheme for users with differentiated QoS requirements. We summarize the common user requirements into four categories: security awareness, service awareness, energy awareness, and load balance, and then introduce the specific implementation methods of various differentiated QoS algorithms. This book provides a variety of VNE solutions, including VNE algorithms for single physical domain, VNE algorithms for across multiple physical domains, VNE algorithms based on heuristic method, and VNE algorithms based on machine learning method.

This book provides a concise and comprehensive overview of vehicular communication technologies. It classifies all relevant standards, protocols and applications, so as to enable the reader to gain a holistic approach towards the subject of vehicular communications. The primary methods are algorithmic processes and simulation results.First, an overview and classification of vehicular technologies is presented. Then, the book focuses on specific applications of V2V and V2I communications. Special attention is given to recent research and development results regarding R&D projects in the field, in cooperation with car manufacturing companies and universities at a global level.Designed to facilitate understanding of vehicle to vehicle and vehicle to infrastructure technologies, this textbook is appropriate for undergraduate and graduate students of vehicular communications or mobile networks.

The study of Wireless Sensor Networks (WSN) is a continually growing, as these networks have the advantage of easy deployment for a number of different applications. Wireless Sensor Networks and Energy Efficiency: Protocols, Routing and Management focuses on wireless sensor networks and their operation, covering topics including routing, energy efficiency and management. Containing 27 chapters authored by a group of internationally experienced professionals and researchers in the fields of computer science, communication, and networking, this book discusses critical issues in wireless sensor network research including MAC, Routing Protocols, TCP, performance and traffic management, time synchronization, and security.

This book provides solution for challenges facing engineers in urban environments looking towards smart development and IoT. The authors address the challenges faced in developing smart applications along with the solutions. Topics addressed include reliability, security and financial issues in relation to all the smart and sustainable development solutions discussed. The solutions they provide are affordable, resistive to threats, and provide high reliability. The book pertains to researchers, academics, professionals, and students. Provides solutions to urban sustainable development problems facing engineers in developing and developed countries Discusses results with industrial problems and current issues in smart city development Includes solutions that are reliable, secure and financially sound

This book provides an interdisciplinary lens for exploring, assessing, and coming to new understandings of smart cities and regions, focusing on the six dimensions of sensing, awareness, learning, openness, innovation, and disruption. Using a hybrid case study and correlational approach, people from diverse sectors in a variety of small to medium to large-sized cities in multiple countries (e.g., Canada, United States, Ireland, Greece, Israel, etc.) provide experience-based perspectives on smart cities together with assessments for elements pertaining to each of the six dimensions. The analysis of findings in this work surfaces a rich and interwoven tapestry of patterns from the qualitative data highlighting for example, the importance of emotion/affect, privacy, trust, and data visualizations in influencing and informing the directions of smart cities and regions going forward. Correlational analysis of quantitative data reveals the presence and strength of emerging relationships among elements assessed, shedding light on factors that may serve as starting points for understanding what is contributing to potentials for improving success in smart cities and regions.

This book explores potentially disruptive and transformative healthcare-specific use cases made possible by the latest developments in Internet of Things (IoT) technology and Cyber-Physical Systems (CPS). Healthcare data can be subjected to a range of different investigations in order to extract highly useful and usable intelligence for the automation of traditionally manual tasks. In addition, next-generation healthcare applications can be enhanced by integrating the latest knowledge discovery and dissemination tools. These sophisticated, smart healthcare applications are possible thanks to a growing ecosystem of healthcare sensors and actuators, new ad hoc and application-specific sensor and actuator networks, and advances in data capture, processing, storage, and mining. Such applications also take advantage of state-of-the-art machine and deep learning algorithms, major strides in artificial and ambient intelligence, and rapid improvements in the stability and maturity of mobile, social, and edge computing models.

The book gathers the best research papers presented at the International Conference on Recent Trends in Communication and Intelligent Systems (ICRTCIS 2019), organized by Rajasthan Technical University Kota, and Arya College of Engineering and IT, Jaipur, on 8-9 June 2019. It discusses the latest technologies in communication and intelligent systems, covering various areas of communication engineering, such as signal processing, VLSI design, embedded systems, wireless communications, and electronics and communications in general. Featuring work by leading researchers and technocrats, the book serves as a valuable reference resource for young researchers and academics as well as practitioners in industry.

This edited book presents point of view and the work being undertaken by active researchers in the domain of IOT and its applications with societal impact. The book is useful to other researchers for the understanding of the research domain and different points of views expressed by the experts in their contributed chapters. The contributions are from both industry and academia; hence, it provides a rich source of both theoretical and practical work going on in the research domain of IOT.

This book mainly discusses the most important issues in artificial intelligence-aided future networks, such as applying different ML approaches to investigate solutions to intelligently monitor, control and optimize networking. The authors focus on four scenarios of successfully applying machine learning in network space. It also discusses the main challenge of network traffic intelligent awareness and introduces several machine learning-based traffic awareness algorithms, such as traffic classification, anomaly traffic identification and traffic prediction. The authors introduce some ML approaches like reinforcement learning to deal with network control problem in this book. Traditional works on the control plane largely rely on a manual process in configuring forwarding, which cannot be employed for today's network conditions. To address this issue, several artificial intelligence approaches for self-learning control strategies are introduced. In addition, resource management problems are ubiquitous in the networking field, such as job scheduling, bitrate adaptation in video streaming and virtual machine placement in cloud computing. Compared with the traditional with-box approach, the authors present some ML methods to solve the complexity network resource allocation problems. Finally, semantic comprehension function is introduced to the network to understand the high-level business intent in this book. With Software-Defined Networking (SDN), Network Function Virtualization (NFV), 5th Generation Wireless Systems (5G) development, the global network is undergoing profound restructuring and transformation. However, with the improvement of the flexibility and scalability of the networks, as well as the ever-increasing complexity of networks, makes effective monitoring, overall control, and optimization of the network extremely difficult. Recently, adding intelligence to the control plane through AI&ML become a trend and a direction of network development This book's expected audience includes professors, researchers, scientists, practitioners, engineers, industry managers, and government research workers, who work in the fields of intelligent network. Advanced-level students studying computer science and electrical engineering will also find this book useful as a secondary textbook.

This book reviews existing operational software failure analysis techniques and proposes near-miss analysis as a novel, and new technique for investigating and preventing software failures. The authors provide details on how near-miss analysis techniques focus on the time-window before the software failure actually unfolds, so as to detect the high-risk conditions that can lead to a major failure. They detail how by alerting system users of an upcoming software failure, the detection of near misses provides an opportunity to collect at runtime failure-related data that is complete and relevant. They present a near-miss management systems (NMS) for detecting upcoming software failures, which can contribute significantly to the improvement of the accuracy of the software failure analysis. A prototype of the NMS is implemented and is discussed in the book. The authors give a practical hands-on approach towards doing software failure investigations by means of near-miss analysis that is of use to industry and academia

Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use. This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies.

This textbook provides engineering students with instruction on processing signals encountered in speech, music, and wireless communications using software or hardware by employing basic mathematical methods. The book starts with an overview of signal processing, introducing readers to the field. It goes on to give instruction in converting continuous time signals into digital signals and discusses various methods to process the digital signals, such as filtering. The author uses MATLAB throughout as a user-friendly software tool to perform various digital signal processing algorithms and to simulate real-time systems. Readers learn how to convert analog signals into digital signals; how to process these signals using software or hardware; and how to write algorithms to perform useful operations on the acquired signals such as filtering, detecting digitally modulated signals, correcting channel distortions, etc. Students are also shown how to convert MATLAB codes into firmware codes. Further, students will be able to apply the basic digital signal processing techniques in their workplace. The book is based on the author's popular online course at University of California, San Diego.

This book focuses on the development and implementation of cloud-based, complex software that allows parallelism, fast processing, and real-time connectivity. Software engineering (SE) is the design, development, testing, and implementation of software applications, and this discipline is as well developed as the practice is well established whereas the Cloud Software Engineering (CSE) is the design, development, testing, and continuous delivery of service-oriented software systems and applications (Software as a Service Paradigm). However, with the emergence of the highly attractive cloud computing (CC) paradigm, the tools and techniques for SE are changing. CC provides the latest software development environments and the necessary platforms relatively easily and inexpensively. It also allows the provision of software applications equally easily and on a pay-as-you-go basis. Business requirements for the use of software are also changing and there is a need for applications in big data analytics, parallel computing, AI, natural language processing, and biometrics, etc. These require huge amounts of computing power and sophisticated data management mechanisms, as well as device connectivity for Internet of Things (IoT) environments. In terms of hardware, software, communication, and storage, CC is highly attractive for developing complex software that is rapidly becoming essential for all sectors of life, including commerce, health, education, and transportation. The book fills a gap in the SE literature by providing scientific contributions from researchers and practitioners, focusing on frameworks, methodologies, applications, benefits and inherent challenges/barriers to engineering software using the CC paradigm.

With classical techniques for data transmission soon reaching their limitations, cognitive approaches may offer a solution to user requirements for better coverage, connectivity, security, and energy efficiency at lower cost. Wireless Sensor Networks: A Cognitive Perspective presents a unified view of the state of the art of cognitive approaches in telecommunications. A benchmark in the field, it brings together research that has previously been scattered throughout conference and journal papers.

Cutting-Edge Topics in Cognitive Communications

After a review of the cognitive concept and approaches, the book outlines a generic architecture for cognition in wireless sensor networks. It then targets specific issues that need to be addressed through cognition, from cognitive radio and spectrum access to routing protocols. The book also explores how to use weighted cognitive maps to improve network lifetime through optimizing routing, medium access, and power control while fulfilling end-to-end goals. The final chapter discusses the implementation of hardware for GPS/INS-enabled wireless sensor networks. This addresses an important need for real-time node position information in many wireless sensor network applications and communication protocols.

Real-World Applications of Wireless Sensor Networks using the Cognitive Concept

Written in a tutorial style, the book supplies an in-depth survey of each topic, accompanied by detailed descriptions of the algorithms and protocols. It also provides a step-by-step analysis of the various communications systems through extensive computer simulations and illustrations. Examples cover environmental monitoring, vehicular communications, tracking, and more. A comprehensive overview of cognitive communications in wireless sensor networks, this work lays the foundations for readers to participate in a new era of research in this emerging field.

This book constitutes the refereed proceedings of the 10th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2018, held in Nanning, China, in October 2018. The 37 full papers and 8 short papers presented were carefully reviewed and selected from 80 submissions. They are organized in topical sections on machine learning, deep learning, multi-agent systems, neural computing and swarm intelligence, natural language processing, recommendation systems, social computing, business intelligence and security, pattern recognition, and image understanding.

The International Conference on Design and Decision Support Systems in Architecture and Urban Planning is organised bi-annually by the Eindhoven University of Technology. This volume contains a selection of papers presented at the eighth conference that was held at the Kapellerput Conference Centre in the village of Heeze, near Eindhoven, The Netherlands, from 4 to 7 July, 2006.

Traditionally, the DDSS conferences aim to be a platform for both starting and experienced researchers who focus on the development and application of computer support in the areas of urban planning and architectural design. This results in an interesting mix of well-established research projects and first explorations. It also leads to a very valuable cross-over of theories, methods, and technologies for support systems in the two different areas, architecture and urban planning. This volume contains 31 peer reviewed papers from this yeara (TM)s conference that are organised into seven sections:

a [ Land Use Simulation and Visualisation

a [ Multi-Agent Models for Movement Simulation

a [ Multi-Agent Models for Urban Development

a [ Managing and Deploying Design Knowledge

a [ Urban Decision-Making

a [ Design Interactivity and Design Automation

a [ Virtual Environments and Augmented Reality.

This book will bring researchers together and is a valuable resource for their continuous joint effort to improve the design and planning of our environment.

This book provides a systematic introduction to the fundamental concepts, major challenges, and effective solutions for Quality of Service in Wireless Sensor Networks (WSNs). Unlike other books on the topic, it focuses on the networking aspects of WSNs, discussing the most important networking issues, including network architecture design, medium access control, routing and data dissemination, node clustering, node localization, query processing, data aggregation, transport and quality of service, time synchronization, and network security. Featuring contributions from researchers, this book strikes a balance between fundamental concepts and new technologies, providing readers with unprecedented insights into WSNs from a networking perspective. It is essential reading for a broad audience, including academics, research engineers, and practitioners, particularly postgraduate/postdoctoral researchers and engineers in industry. It is also suitable as a textbook or supplementary reading for graduate computer engineering and computer science courses.