Artificial Intelligence for Cyber-Physical Systems Hardening

This book explores new machine learning and artificial intelligence approaches and technologies for securing cyber-physical systems, presenting fundamental AI/ML principles and case studies. It is a valuable resource for students, instructors, researchers, industry practitioners, and government agencies.

Format: Hardback
Length: 233 pages
Publication date: 24 November 2022
Publisher: Springer International Publishing AG

Cyber-physical systems (CPS) are a rapidly evolving field that combines the principles of software, sensors, and actuators to create integrated systems that can interact with the physical world. These systems are becoming increasingly important in various industries, such as transportation, healthcare, and manufacturing, as they enable the automation of processes, improve efficiency, and enhance safety. However, the development of secure and trustworthy CPS poses significant challenges, as these systems are vulnerable to a wide range of threats, including cyberattacks, physical tampering, and human error.

To address these challenges, researchers and industry practitioners have been developing new machine learning (ML) and artificial intelligence (AI) approaches and technologies. These approaches aim to improve the security and trustworthiness of CPS by enabling them to detect and respond to threats in real-time.

This book presents advances in security assurance for cyber-physical systems and reports on new ML and AI approaches and technologies developed by the research community and the industry. It covers a wide range of topics, including:

Fundamental AI/ML principles and concepts applied in developing secure and trustworthy CPS.

Recent research and development efforts in this fascinating area.

Relevant case studies, examples, and datasets.

The book is organized into five chapters, each covering a different aspect of security assurance for CPS. Chapter 1 provides an introduction to the field of CPS and discusses the challenges faced by these systems. Chapter 2 introduces fundamental AI/ML principles and concepts applied in developing secure and trustworthy CPS. Chapter 3 discusses recent research and development efforts in this area, including machine learning algorithms, deep learning techniques, and natural language processing. Chapter 4 presents relevant case studies, examples, and datasets that demonstrate the practical applications of AI/ML in developing secure and trustworthy CPS. Chapter 5 concludes the book by discussing future directions and challenges in this field.

We believe that this book is a valuable reference for students, instructors, researchers, industry practitioners, and related government agencies staff. It provides a comprehensive overview of the latest developments in security assurance for cyber-physical systems and offers insights into the future of this exciting field.

Introduction:

Cyber-physical systems (CPS) are a rapidly evolving field that combines the principles of software, sensors, and actuators to create integrated systems that can interact with the physical world. These systems are becoming increasingly important in various industries, such as transportation, healthcare, and manufacturing, as they enable the automation of processes, improve efficiency, and enhance safety. However, the development of secure and trustworthy CPS poses significant challenges, as these systems are vulnerable to a wide range of threats, including cyberattacks, physical tampering, and human error.

To address these challenges, researchers and industry practitioners have been developing new machine learning (ML) and artificial intelligence (AI) approaches and technologies. These approaches aim to improve the security and trustworthiness of CPS by enabling them to detect and respond to threats in real-time.

This book presents advances in security assurance for cyber-physical systems and reports on new ML and AI approaches and technologies developed by the research community and the industry. It covers a wide range of topics, including:

Fundamental AI/ML principles and concepts applied in developing secure and trustworthy CPS:

Chapter 1 provides an introduction to the field of CPS and discusses the challenges faced by these systems. Chapter 2 introduces fundamental AI/ML principles and concepts applied in developing secure and trustworthy CPS. Chapter 3 discusses recent research and development efforts in this area, including machine learning algorithms, deep learning techniques, and natural language processing. Chapter 4 presents relevant case studies, examples, and datasets that demonstrate the practical applications of AI/ML in developing secure and trustworthy CPS. Chapter 5 concludes the book by discussing future directions and challenges in this field.

Conclusion:

We believe that this book is a valuable reference for students, instructors, researchers, industry practitioners, and related government agencies staff. It provides a comprehensive overview of the latest developments in security assurance for cyber-physical systems and offers insights into the future of this exciting field.

Weight: 541g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031162367
Edition number: 1st ed. 2023