Deception In Autonomous Transport Systems

This book provides a comprehensive overview of deception in autonomous transport systems. This involves investigating the threats facing autonomous transport systems and how they can contribute towards a deceptive attack, followed by their potential impact if successful, and finally, how they can be mitigated. The work in this book is grouped into three parts. This first part focuses on the area of smart cities, policies, and ethics. This includes critically appraising the trade-off between functionality and security with connected and autonomous vehicles. The second discusses a range of AI applications in the wider field of smart transport and mobility, such as detecting anomalies in vehicle behaviour to investigating detecting disobedient vehicles. Finally, the third part presents and discusses cybersecurity-related aspects to consider when dealing with Connected and Autonomous Vehicles (CAVs) and smart urban infrastructure. This includes analysing different attacks to investigating secure communication technologies. CAVs are a game-changing technology with the potential to transform the way transport is perceived, mobility is serviced, travel ecosystems ‘behave’, and cities and societies as a whole function. There are many foreseen safety, accessibility and sustainability benefits resulting from the adoption of CAVs because of their ability, in theory, to operate error-free and collaboratively, ranging from accident prevention, congestion reduction and decreased carbon emissions to time savings, increased social inclusion, optimised routing, and better traffic control. However, no matter what the expected benefits are, CAVs are at the same time susceptible to an unprecedented number of new digital and physical threats. The severity of these threats has resulted in an increased effort to deepen our understanding of CAVs when it comes to their safety and resilience. In this complex and multi-faceted scenario, this book aims to provide an extensive overview of the risks related to the malicious exploitation of CAVs and beyond, the potential ways in which vulnerabilities can be exploited, prevention and mitigation policies and techniques, and the impact that the non-acceptance of Connected and Autonomous Mobility can have on the Smart City agenda. This book targets researchers, practitioners, and advanced-level students in computer science and transport engineering.

This is the first comprehensive book on the autonomous vehicles as a part of the smart transportation systems. It was written by scientists and engineers who had been actively contributing to the development of technical knowledge in this field. The authors tried to cover both the theoretical background and the multitude of practical issues related to either commercially-available or laboratory-validated vehicular technologies. The book will be invaluable not only for engineers directly concerned with the development of autonomous vehicles, but also to those who are interested in various fields that overlap with these specific topics: power engineering, electrical drives, control systems, sensors and actuators and artificial intelligence. Technical executives concerned with intelligent transportation systems will also find it timely and important.

This textbook surveys the knowledge base in automated and resilient cyber deception. It features four major parts: cyber deception reasoning frameworks, dynamic decision-making for cyber deception, network-based deception, and malware deception. An important distinguishing characteristic of this book is its inclusion of student exercises at the end of each chapter. Exercises include technical problems, short-answer discussion questions, or hands-on lab exercises, organized at a range of difficulties from easy to advanced,. This is a useful textbook for a wide range of classes and degree levels within the security arena and other related topics. It’s also suitable for researchers and practitioners with a variety of cyber security backgrounds from novice to experienced.

While many transportation and city planners, researchers, students, practitioners, and political leaders are familiar with the technical nature and promise of vehicle automation, consensus is not yet often seen on the impact that will result, or the policies and actions that those responsible for transportation systems should take. The End of Driving: Transportation Systems and Public Policy Planning for Autonomous Vehicles explores both the potential of vehicle automation technology and the barriers it faces when considering coherent urban deployment. The book evaluates the case for deliberate development of automated public transportation and mobility-as-a-service as paths towards sustainable mobility, describing critical approaches to the planning and management of vehicle automation technology. It serves as a reference for understanding the full life cycle of the multi-year transportation systems planning processes, including novel regulation, planning, and acquisition tools for regional transportation. Application-oriented, research-based, and solution-oriented rather than predict-and-warn, The End of Driving concludes with a detailed discussion of the systems design needed for accomplishing this shift. From the Foreword by Susan Shaheen: The authors ... extend potential solutions through a set of open-ended exercises after each chapter. Their approach is both strategic and deliberate. They lead the reader from definitions and context setting to the transition toward automation, employing a range of creative strategies and policies. While our quest to understand how to deploy automated vehicles is just beginning, this book provides a thoughtful introduction to inform this evolution. Offers a workable public transit solution design melding the traditional “acquire-and-operate mode with the absorption of new technology Provides a step-by-step discussion of digital systems designs and effective regulation-by-data approaches needed for a new urban mobility Learning aids include case study scenarios, chapter objectives and discussion questions, sidebars and a glossary

This book introduces a cross-layer design to achieve security and resilience for CPSs (Cyber-Physical Systems). The authors interconnect various technical tools and methods to capture the different properties between cyber and physical layers. Part II of this book bridges the gap between cryptography and control-theoretic tools. It develops a bespoke crypto-control framework to address security and resiliency in control and estimation problems where the outsourcing of computations is possible. Part III of this book bridges the gap between game theory and control theory and develops interdependent impact-aware security defense strategies and cyber-aware resilient control strategies. With the rapid development of smart cities, there is a growing need to integrate the physical systems, ranging from large-scale infrastructures to small embedded systems, with networked communications. The integration of the physical and cyber systems forms Cyber-Physical Systems (CPSs), enabling the use of digital information and control technologies to improve the monitoring, operation, and planning of the systems. Despite these advantages, they are vulnerable to cyber-physical attacks, which aim to damage the physical layer through the cyber network. This book also uses case studies from autonomous systems, communication-based train control systems, cyber manufacturing, and robotic systems to illustrate the proposed methodologies. These case studies aim to motivate readers to adopt a cross-layer system perspective toward security and resilience issues of large and complex systems and develop domain-specific solutions to address CPS challenges. A comprehensive suite of solutions to a broad range of technical challenges in secure and resilient control systems are described in this book (many of the findings in this book are useful to anyone working in cybersecurity). Researchers, professors, and advanced-level students working in computer science and engineering will find this book useful as a reference or secondary text. Industry professionals and military workers interested in cybersecurity will also want to purchase this book.

The book provides a broad overview of the challenges and recent developments in the field of smart mobility and transportation, including technical, algorithmic and social aspects of smart mobility and transportation. It reviews new ideas for services and platforms for future mobility. New concepts of artificial intelligence and the implementation in new hardware architecture are discussed. In the context of artificial intelligence, new challenges of machine learning for autonomous vehicles and fleets are investigated. The book also investigates human factors and social questions of future mobility concepts. The goal of this book is to provide a holistic approach towards smart transportation. The book reviews new technologies such as the cloud, machine learning and communication for fully atomatized transport, catering to the needs of citizens. This will lead to complete change of concepts in transportion.

Human-Machine Shared Contexts considers the foundations, metrics, and applications of human-machine systems. Editors and authors debate whether machines, humans, and systems should speak only to each other, only to humans, or to both and how. The book establishes the meaning and operation of “shared contexts between humans and machines; it also explores how human-machine systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems composed of humans and machines. This book explores how user interventions may improve the context for autonomous machines operating in unfamiliar environments or when experiencing unanticipated events; how autonomous machines can be taught to explain contexts by reasoning, inferences, or causality, and decisions to humans relying on intuition; and for mutual context, how these machines may interdependently affect human awareness, teams and society, and how these "machines" may be affected in turn. In short, can context be mutually constructed and shared between machines and humans? The editors are interested in whether shared context follows when machines begin to think, or, like humans, develop subjective states that allow them to monitor and report on their interpretations of reality, forcing scientists to rethink the general model of human social behavior. If dependence on machine learning continues or grows, the public will also be interested in what happens to context shared by users, teams of humans and machines, or society when these machines malfunction. As scientists and engineers "think through this change in human terms," the ultimate goal is for AI to advance the performance of autonomous machines and teams of humans and machines for the betterment of society wherever these machines interact with humans or other machines. This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning (ML) and artificial intelligence (AI) scientists and engineers, especially those engaged in research on autonomy, computational context, and human-machine shared contexts; advanced robotics scientists and engineers; scientists working with or interested in data issues for autonomous systems such as with the use of scarce data for training and operations with and without user interventions; social psychologists, scientists and physical research scientists pursuing models of shared context; modelers of the internet of things (IOT); systems of systems scientists and engineers and economists; scientists and engineers working with agent-based models (ABMs); policy specialists concerned with the impact of AI and ML on society and civilization; network scientists and engineers; applied mathematicians (e.g., holon theory, information theory); computational linguists; and blockchain scientists and engineers. Discusses the foundations, metrics, and applications of human-machine systems Considers advances and challenges in the performance of autonomous machines and teams of humans Debates theoretical human-machine ecosystem models and what happens when machines malfunction