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Author: Hadis Karimipour
Publisher: Springer Nature
ISBN: 3030766136
Category : Computers
Languages : en
Pages : 250
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Book Description
This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and Machine Learning (ML) can be used to address these challenges. Furthermore, this book proposes various defence strategies, including intelligent cyber-attack and anomaly detection algorithms for different IIoT applications. Each chapter corresponds to an important snapshot including an overview of the opportunities and challenges of realizing the AI in IIoT environments, issues related to data security, privacy and application of blockchain technology in the IIoT environment. This book also examines more advanced and specific topics in AI-based solutions developed for efficient anomaly detection in IIoT environments. Different AI/ML techniques including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning and multi-stage learning are discussed and analysed as well. Researchers and professionals working in computer security with an emphasis on the scientific foundations and engineering techniques for securing IIoT systems and their underlying computing and communicating systems will find this book useful as a reference. The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, cyber security, and information systems. It also applies to advanced-level students studying electrical engineering and system engineering, who would benefit from the case studies.
Author: Hadis Karimipour
Publisher: Springer Nature
ISBN: 3030766136
Category : Computers
Languages : en
Pages : 250
Get Book Here
Book Description
This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and Machine Learning (ML) can be used to address these challenges. Furthermore, this book proposes various defence strategies, including intelligent cyber-attack and anomaly detection algorithms for different IIoT applications. Each chapter corresponds to an important snapshot including an overview of the opportunities and challenges of realizing the AI in IIoT environments, issues related to data security, privacy and application of blockchain technology in the IIoT environment. This book also examines more advanced and specific topics in AI-based solutions developed for efficient anomaly detection in IIoT environments. Different AI/ML techniques including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning and multi-stage learning are discussed and analysed as well. Researchers and professionals working in computer security with an emphasis on the scientific foundations and engineering techniques for securing IIoT systems and their underlying computing and communicating systems will find this book useful as a reference. The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, cyber security, and information systems. It also applies to advanced-level students studying electrical engineering and system engineering, who would benefit from the case studies.
Author: Sunil Kumar Chawla
Publisher: CRC Press
ISBN: 1040146759
Category : Computers
Languages : en
Pages : 247
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Book Description
The industrial landscape is changing rapidly, and so is global society. This change is driven by the growing adoption of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) technologies. IIoT and AI are transforming the way industrial engineering is done, enabling new levels of automation, productivity, and efficiency. However, as IIoT and AI become more pervasive in the industrial world, they also offer new security risks that must be addressed to ensure the reliability and safety of critical systems. Industrial Internet of Things Security: Protecting AI-Enabled Engineering Systems in Cloud and Edge Environments provides a comprehensive guide to IIoT security, covering topics such as network architecture, risk management, data security, and compliance. It addresses the unique security challenges that the cloud and edge environments pose, providing practical guidance for securing IIoT networks in these contexts. It includes numerous real-world case studies and examples, providing readers with practical insights into how IIoT security and AI-enabled industrial engineering are being implemented in various industries. Best practices are emphasized for the readers to ensure the reliability, safety, and security of their systems while also learning the latest developments in IIoT security for AI-enabled industrial engineering systems in this rapidly evolving field. By offering step-by-step guidance for the implantation process along with best practices, this book becomes a valuable resource for practitioners and engineers in the areas of industrial engineering, IT, computer engineering, and anyone looking to secure their IIoT network against cyber threats.
Author: Pethuru Raj
Publisher: CRC Press
ISBN: 1040026060
Category : Computers
Languages : en
Pages : 580
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Book Description
Modern enterprises are facing growing cybersecurity issues due to the massive volume of security-related data they generate over time. AI systems can be developed to resolve a range of these issues with comparative ease. This new book describes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help eliminate them. With chapters from industry and security experts, this volume discribes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help elimintate them. With chapters from industry and security experts, this volume discusses the many new and emerging AI technologies and approaches that can be harnessed to combat cyberattacks, including big data analytics techniques, deep neural networks, cloud computer networks, convolutional neural networks, IoT edge devices, machine learning approaches, deep learning, blockchain technology, convolutional neural networks, and more. Some unique features of this book include: Detailed overview of various security analytics techniques and tools Comprehensive descriptions of the emerging and evolving aspects of artificial intelligence (AI) technologies Industry case studies for practical comprehension and application This book, Leveraging the Artificial Intelligence Competencies for Next-Generation Cybersecurity Solutions, illustrates how AI is a futuristic and flexible technology that can be effectively used for tackling the growing menace of cybercriminals. It clearly demystifies the unique contributions of AI algorithms, models, frameworks, and libraries in nullifying the cyberattacks. The volume will be a valuable resource for research students, scholars, academic professors, business executives, security architects, and consultants in the IT industry.
Author: Masoud Abbaszadeh
Publisher: Springer Nature
ISBN: 303097166X
Category : Technology & Engineering
Languages : en
Pages : 383
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Book Description
This book discusses the latest advances in cyber-physical security and resilience of cyber-physical systems, including cyber-attack detection, isolation, situation awareness, resilient estimation and resilient control under attack. It presents both theoretical results and important applications of the methods. Security and Resilience in Cyber-Physical Systems begins by introducing the topic of cyber-physical security, covering state-of-the-art trends in both theory and applications, as well as some of the emerging methodologies and future directions for research. It then moves on to detail theoretical methods of attack detection, resilient estimation and control within cyber-physical systems, before discussing their various applications, such as power generation and distribution, autonomous systems, wireless communication networks and chemical plants. Focusing on the detection of and accommodation to cyber-attacks on cyber-physical systems, and including both estimation and artificial-intelligence-based methods, this book will be of interest to researchers, engineers and graduate students within the fields of cyber-physical security and resilient control.
Author: Prodipto Das
Publisher: Springer Nature
ISBN: 3031472217
Category :
Languages : en
Pages : 302
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Book Description
Author: De-Shuang Huang
Publisher: Springer Nature
ISBN: 9819755883
Category :
Languages : en
Pages : 536
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Book Description
Author: Éric Renault
Publisher: Springer Nature
ISBN: 3031361830
Category : Computers
Languages : en
Pages : 190
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Book Description
This book constitutes the post-conference proceedings of the 5th International Conference on Machine Learning for Networking, MLN 2022, held in Paris, France, November 28–30, 2022. The 12 full papers presented in this book were carefully reviewed and selected from 27 submissions. The papers present novel ideas, results, experiences and work-in-process on all aspects of Machine Learning and Networking.
Author: Paramartha Dutta
Publisher: Springer Nature
ISBN: 9811946760
Category : Technology & Engineering
Languages : en
Pages : 670
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Book Description
This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2022) held at Institute of Engineering & Management, Kolkata, India, during February 23–25, 2022. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of Things (IoT), and information security.
Author: Pushan Kumar Dutta
Publisher: CRC Press
ISBN: 1040125166
Category : Computers
Languages : en
Pages : 465
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Book Description
Smart manufacturing environments are revolutionizing the industrial sector by integrating advanced technologies, such as the Internet of Things (IoT), artificial intelligence (AI), and robotics, to achieve higher levels of efficiency, productivity, and safety. However, the increasing complexity and interconnectedness of these systems also introduce new security challenges that must be addressed to ensure the safety of human workers and the integrity of manufacturing processes. Key topics include risk assessment methodologies, secure communication protocols, and the development of standard specifications to guide the design and implementation of HCPS. Recent research highlights the importance of adopting a multi-layered approach to security, encompassing physical, network, and application layers. Furthermore, the integration of AI and machine learning techniques enables real-time monitoring and analysis of system vulnerabilities, as well as the development of adaptive security measures. Artificial Intelligence Solutions for Cyber-Physical Systems discusses such best practices and frameworks as NIST Cybersecurity Framework, ISO/IEC 27001, and IEC 62443 of advanced technologies. It presents strategies and methods to mitigate risks and enhance security, including cybersecurity frameworks, secure communication protocols, and access control measures. The book also focuses on the design, implementation, and management of secure HCPS in smart manufacturing environments. It covers a wide range of topics, including risk assessment, security architecture, data privacy, and standard specifications, for HCPS. The book highlights the importance of securing communication protocols, the role of artificial intelligence and machine learning in threat detection and mitigation, and the need for robust cybersecurity frameworks in the context of smart manufacturing.
Author: Radek Silhavy
Publisher: Springer Nature
ISBN: 3031705181
Category :
Languages : en
Pages : 722
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Book Description
