Artificial Intelligence Paradigms for Smart Cyber-Physical Systems
Artificial Intelligence Paradigms for Smart Cyber-Physical Systems

Author: Luhach, Ashish Kumar

Publisher: IGI Global

Published: 2020-11-13

Total Pages: 392

ISBN-13: 1799851028

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Cyber-physical systems (CPS) have emerged as a unifying name for systems where cyber parts (i.e., the computing and communication parts) and physical parts are tightly integrated, both in design and during operation. Such systems use computations and communication deeply embedded in and interacting with human physical processes as well as augmenting existing and adding new capabilities. As such, CPS is an integration of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. The economic and societal potential of such systems is vastly greater than what has been realized, and major investments are being made worldwide to develop the technology. Artificial Intelligence Paradigms for Smart Cyber-Physical Systems focuses on the recent advances in Artificial intelligence-based approaches towards affecting secure cyber-physical systems. This book presents investigations on state-of-the-art research issues, applications, and achievements in the field of computational intelligence paradigms for CPS. Covering topics that include autonomous systems, access control, machine learning, and intrusion detection and prevention systems, this book is ideally designed for engineers, industry professionals, practitioners, scientists, managers, students, academicians, and researchers seeking current research on artificial intelligence and cyber-physical systems.

Intelligent Security Solutions for Cyber-Physical Systems
Intelligent Security Solutions for Cyber-Physical Systems

Author: Vandana Mohindru Sood

Publisher: CRC Press

Published: 2024-04-22

Total Pages: 282

ISBN-13: 1040011888

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A cyber-physical system (CPS) is a computer system in which a mechanism is controlled or monitored by computer-based algorithms and involves transdisciplinary approaches, merging theories of cybernetics, mechatronics, design, and process science. This text mainly concentrates on offering a foundational theoretical underpinning, and a comprehensive and coherent review of intelligent security solutions for cyber-physical systems. Features: Provides an overview of cyber-physical systems (CPSs) along with security concepts like attack detection methods, cyber-physical systems failures, and risk identification and management Showcases cyber-physical systems (CPSs) security solutions, lightweight cryptographic solutions, and CPS forensics, etc Emphasizes machine learning methods for behavior-based intrusion detection in cyber-physical systems (CPSs), resilient machine learning for networked CPS, fog computing industrial CPS, etc Elaborates classification of network abnormalities in Internet of Things-based cyber-physical systems (CPSs) using deep learning Includes case studies and applications in the domain of smart grid systems, industrial control systems, smart manufacturing, social network and gaming, electric power grid and energy systems, etc

Blockchain based Internet of Things
Blockchain based Internet of Things

Author: Debashis De

Publisher: Springer Nature

Published: 2022-03-01

Total Pages: 313

ISBN-13: 9811692602

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The book is aimed to foster knowledge based on Blockchain technology highlighting on the framework basics, operating principles and different incarnations. The fundamental problems encountered in existing blockchain architectures and means for removing those would be covered. It would also touch upon blockchain based IoT systems and applications. The book covers applications and use cases of blockchain technology for industrial IoT systems. In addition, methods for inducing computational intelligence into existing blockchain frameworks thereby thwarting most of the limitations are also discussed. The readers would benefit from the rich technical content in this rapidly emerging field thereby enabling a skilled workforce for the future.

Emerging Trends for Securing Cyber Physical Systems and the Internet of Things
Emerging Trends for Securing Cyber Physical Systems and the Internet of Things

Author: Bharat Bhushan

Publisher: CRC Press

Published: 2024-05-09

Total Pages: 271

ISBN-13: 1040022278

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In the past decades, cyber-physical systems (CPSs) have been widely applied to fields such as smart grids, environment monitoring, aerospace, smart transportation, and industrial automation. Great strides have been made in CPSs to improve the computing mechanism, communication, and quality of service by applying optimization algorithms. Currently, these efforts are integrated with the applications of machine learning (ML) and artificial intelligence (AI). To maintain system reliability and stability, CPSs such as smart grids face numerous challenges, including large-scale Internet-of-Things (IoT) device adaptation, ever-increasing demands of electrical energy, and the rise of a wide range of security threats. These challenges bring forth the need to find sustainable and advanced solutions to guarantee reliable and secure operations in these systems. The goal of this book is to foster transformative, multidisciplinary, and novel approaches that ensure CPS security by taking into consideration the unique security challenges present in the environment. This book attracts contributions in all aspects pertaining to this multidisciplinary paradigm, which includes the development and implementation of Smart CPS, Supervisory Control and Data Acquisition (SCADA) systems, CPS for Industry 4.0, CPS architecture for IoT applications, and CPS forensics. This book: Discusses concepts including wireless sensor networks (WSNs), CPSs, and the IoT in a comprehensive manner. Covers routing protocols in sensor networks, attacks, and vulnerabilities in WSNs, the Internet of Cyber-Physical Things, and CPSs for industrial applications. Highlights technological advances, practical solutions, emerging trends, and prototypes related to privacy in CPSs and the IoT. Presents a pathway and architecture for proactive security schemes in CPSs to counter vulnerabilities, including phishing attacks, malware injection, internal stealing of data, and hacking. Discusses the most recent research and development on the enabling technologies for IoT-based CPSs. Owing to the scope and diversity of topics covered, the book will be of interest not only to researchers and theorists but also to professionals, material developers, technology specialists, and methodologists dealing with the multifarious aspects of data privacy and security enhancement in CPSs. The book will provide these professionals an overview of CPS security and privacy design, as well as enlighten them to promising solutions to research problems such as cyberattacks in CPS, risk identification and management in CPS, ML-based trust computational models for CPSs, nature-inspired algorithms for CPSs, and distributed consensus algorithms for event detection in CPSs. The secondary target audience of this book includes legal practitioners, hackers, cyber law policymakers, cyber forensic analysts, and global security consortiums who may use it to further their research exposure to pertinent topics in cybersecurity.

Artificial Intelligence for Robotics and Autonomous Systems Applications
Artificial Intelligence for Robotics and Autonomous Systems Applications

Author: Ahmad Taher Azar

Publisher: Springer Nature

Published: 2023-05-15

Total Pages: 488

ISBN-13: 3031287150

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This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics. Artificial intelligence is being integrated into robots in order to develop advanced robotics capable of performing multiple tasks and learning new things with a better perception of the environment, allowing robots to perform critical tasks with human-like vision to detect or recognize various objects. Intelligent robots have been successfully constructed using machine learning and deep learning AI technology. Robotics performance is improving as higher quality, and more precise machine learning processes are used to train computer vision models to recognize different things and carry out operations correctly with the desired outcome. We believe that the increasing demands and challenges offered by real-world robotic applications encourage academic research in both artificial intelligence and robotics. The goal of this book is to bring together scientists, specialists, and engineers from around the world to present and share their most recent research findings and new ideas on artificial intelligence in robotics.

Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection
Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection

Author: Shilpa Mahajan

Publisher: John Wiley & Sons

Published: 2024-03-22

Total Pages: 373

ISBN-13: 1394196466

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APPLYING ARTIFICIAL INTELLIGENCE IN CYBERSECURITY ANALYTICS AND CYBER THREAT DETECTION Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML) Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats. Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter. With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection explores topics such as: Cybersecurity tools originating from computational statistics literature and pure mathematics, such as nonparametric probability density estimation, graph-based manifold learning, and topological data analysis Applications of AI to penetration testing, malware, data privacy, intrusion detection system (IDS), and social engineering How AI automation addresses various security challenges in daily workflows and how to perform automated analyses to proactively mitigate threats Offensive technologies grouped together and analyzed at a higher level from both an offensive and defensive standpoint Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.

TinyML for Edge Intelligence in IoT and LPWAN Networks
TinyML for Edge Intelligence in IoT and LPWAN Networks

Author: Bharat S Chaudhari

Publisher: Elsevier

Published: 2024-05-29

Total Pages: 520

ISBN-13: 0443222037

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Recently, Tiny Machine Learning (TinyML) has gained incredible importance due to its capabilities of creating lightweight machine learning (ML) frameworks aiming at low latency, lower energy consumption, lower bandwidth requirement, improved data security and privacy, and other performance necessities. As billions of battery-operated embedded IoT and low power wide area networks (LPWAN) nodes with very low on-board memory and computational capabilities are getting connected to the Internet each year, there is a critical need to have a special computational framework like TinyML. TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to IoT and LPWANs. It starts by providing the foundations of IoT/LPWANs, low power embedded systems and hardware, the role of artificial intelligence and machine learning in communication networks in general and cloud/edge intelligence. It then presents the concepts, methods, algorithms and tools of TinyML. Practical applications of the use of TinyML are given from health and industrial fields which provide practical guidance on the design of applications and the selection of appropriate technologies. TinyML for Edge Intelligence in IoT and LPWAN Networks is highly suitable for academic researchers and professional system engineers, architects, designers, testers, deployment engineers seeking to design ultra-lower power and time-critical applications. It would also help in designing the networks for emerging and future applications for resource-constrained nodes. - This book provides one-stop solutions for emerging TinyML for IoT and LPWAN applications. - The principles and methods of TinyML are explained, with a focus on how it can be used for IoT, LPWANs, and 5G applications. - Applications from the healthcare and industrial sectors are presented. - Guidance on the design of applications and the selection of appropriate technologies is provided.

Machine Learning for Sustainable Manufacturing in Industry 4.0
Machine Learning for Sustainable Manufacturing in Industry 4.0

Author: Raman Kumar

Publisher: CRC Press

Published: 2023-11-03

Total Pages: 250

ISBN-13: 1000986195

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The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods. Focusses on machine learning applications in Industry 4.0 ecosystem, such as resource optimization, data analysis, and predictions. Highlights the importance of the explainable machine learning model in the manufacturing processes. Presents the integration of machine learning and big data analytics from an industry 4.0 perspective. Discusses advanced computational techniques for sustainable manufacturing. Examines environmental impacts of operations and supply chain from an industry 4.0 perspective. This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.

Cyberbiosecurity
Cyberbiosecurity

Author: Dov Greenbaum

Publisher: Springer Nature

Published: 2023-05-09

Total Pages: 308

ISBN-13: 3031260341

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Cyberbiosecurity applies cybersecurity research to the field of biology, and, to a lesser degree, applies biological principles to the field of cybersecurity. As biologists increasingly research, collaborate, and conduct research online, cyberbiosecurity has become crucial to protect against cyber threats. This book provides an overview of cyberbiosecurity through the lens of researchers in academia, industry professionals, and government, in both biology and cybersecurity fields. The book highlights emerging technologies, and identifies emerging threats connected with these technologies, while also providing a discussion of the legal implications involved. This book takes on a multidisciplinary approach, and appeals to both professionals and researchers in the synthetic biology, bioinformatics, and cybersecurity fields.

Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms

Author: Milutinovi?, Veljko

Publisher: IGI Global

Published: 2022-03-11

Total Pages: 296

ISBN-13: 1799883523

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Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.