2018 Acm Ieee 9th International Conference On Cyber Physical Systems Iccps

ACM IEEE ICCPS is the premier single track conference for reporting advances in all CPS aspects, including theory, tools, applications, systems, test beds and field deployments

This book explores the intersection of blockchain technology, artificial intelligence (AI) and cyber physical systems (CPS). It discusses how these technologies can be integrated to create secure and efficient CPS solutions. The book covers various topics, including the basics of blockchain and AI, their applications in CPS and the challenges of integrating these technologies. It also explores real-world examples of how blockchain and AI are used in CPS, such as smart cities, transportation systems and healthcare. The authors delve into the technical aspects of how blockchain and AI can be used together to enhance CPS security, data privacy and interoperability. They also discuss the potential benefits and limitations of these technologies and provide insights into the future of CPS. Overall, this book provides a comprehensive overview of the use of blockchain and AI in CPS, making it a valuable resource for researchers, professionals and students in the fields of computer science, engineering and cybersecurity.

ACM/IEEE 1st International Conference on Cyber-Physical Systems Apr 12, 2010-Apr 15, 2010 Stockholm, Sweden. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

This new work explores the growth of information and communication technologies with an emphasis on cyber-physical systems and security management of these systems. This volume discusses and analyzes the various effective practical applications of CPS, which involves the integration of the physical process with embedded computation and network monitoring along with feedback loops from physical systems. The authors identify the best set of applications and discuss the drawbacks of existing systems. The book provides a broad outlook on the applications of cyber-physical systems along with case studies and examples in healthcare, automotive electronics, industrial automation, environment monitoring, agriculture, and applications in civil and mechanical sectors. Topics include using an energy management system in smart grids, implementing an intelligent traffic management system, warehouse tracking and monitoring, medical cyber-physical systems security, remote healthcare monitoring, and more.

This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.

A graduate-level textbook that presents a unified mathematical framework for modeling and analyzing cyber-physical systems, with a strong focus on verification. Verification aims to establish whether a system meets a set of requirements. For such cyber-physical systems as driverless cars, autonomous spacecraft, and air-traffic management systems, verification is key to building safe systems with high levels of assurance. This graduate-level textbook presents a unified mathematical framework for modeling and analyzing cyber-physical systems, with a strong focus on verification. It distills the ideas and algorithms that have emerged from more than three decades of research and have led to the creation of industrial-scale modeling and verification techniques for cyber-physical systems. The book discusses such computer science concepts as undecidability and abstractions, alongside concepts from control theory including multiple Lyapunov functions and barrier certificates, all within a unified mathematical language. It explains algorithms for reachability analysis, counter-example guided abstraction refinement, and data-driven verification, as well as the key data structures that enable their effective implementation. Other topics include invariants, deductive verification, progress analysis, sensitivity analysis, simulation relations, fairness, model checking, satisfiability modulo theories, temporal logics, compositional reasoning, convergence analysis, asynchronous processes, and verification of black-box systems.The book provides more than twenty examples of cyber-physical verification, ranging from conceptual models to advanced driving-assist systems. Each chapter offers exercise problems; supporting materials, including slides, simulation code, additional exercises, and solutions are available on the book's website.

This book offers a structured overview and a comprehensive guide to the emerging field of Autonomous Intelligent Cyber Defense Agents (AICA). The book discusses the current technical issues in autonomous cyber defense and offers information on practical design approaches. The material is presented in a way that is accessible to non-specialists, with tutorial information provided in the initial chapters and as needed throughout the book. The reader is provided with clear and comprehensive background and reference material for each aspect of AICA. Today’s cyber defense tools are mostly watchers. They are not active doers. They do little to plan and execute responses to attacks, and they don’t plan and execute recovery activities. Response and recovery – core elements of cyber resilience – are left to human cyber analysts, incident responders and system administrators. This is about to change. The authors advocate this vision, provide detailed guide to how such a vision can be realized in practice, and its current state of the art. This book also covers key topics relevant to the field, including functional requirements and alternative architectures of AICA, how it perceives and understands threats and the overall situation, how it plans and executes response and recovery, how it survives threats, and how human operators deploy and control AICA. Additionally, this book covers issues of testing, risk, and policy pertinent to AICA, and provides a roadmap towards future R&D in this field. This book targets researchers and advanced students in the field of cyber defense and resilience. Professionals working in this field as well as developers of practical products for cyber autonomy will also want to purchase this book.

This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.