1st Edition

Industrial Internet of Things Security Protecting AI-Enabled Engineering Systems in Cloud and Edge Environments

    272 Pages 58 B/W Illustrations
    by CRC Press

    The industrial landscape is changing rapidly, and so is the 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 for 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.

    1. Protecting AI-enabled Industrial Engineering in Cloud and Edge Environments. 2. Industrial Internet of Things Security Architecture and Protection Techniques. 3. Exploring Risk Management in Industrial Systems. 4.Data Security for Industrial Internet of Things: An Essential Perspective for Industrial Engineering. 5. Navigating Compliance for the Industrial IoT Landscape: Frameworks, Security, Standards, and Key Ethical Considerations. 6. Lightweight Secure key Authentication Scheme for Industrial Internet of Things. 7. DLIoT: A Deep Learning Approach for Enhancing Security in Industrial IoT. 8. Elevating Industries: Cloud Computing's Impact on Industry-Integrated IoT. 9. Edge, IIOT with AI: Transforming Industrial Engineering and Minimising security threat. 10. The Convergence of Medical IoT and Patient Privacy: Challenges and Solutions. 11. Towards a Trusted Smart City Ecosystem: IoE and Blockchain-Enabled Cognitive Frameworks for Shared Business Services.


    Dr. Sunil Kumar Chawla is working as an Assistant Professor in the Department of Computer Science and Engineering, at Chitkra University, Rajpura, Punjab, India. He has received his doctorate from IKG Punjab Technical University, Kapurthala, Punjab, India. His research interests lie in Digital Image Processing, Biometrics, Image Segmentation, and Machine Learning and Pattern Recognition. He is a member of IEEE and other professional societies like ISTE, CSTA, IAENG, TERA, and the Institute of Scholars. He has more than 40 publications in international journals of repute. Dr. Chawla is associated with various international journals in the capacity of reviewer and guest editor and has served as a Technical Program Committee Member, Reviewer, Session Chair, and Program Chair of many conferences. He has edited two books and is involved in various academic and administrative duties for the inclusive growth of the institution by handling teaching, learning, research, education, and overall development activities. He participates in NBA, NAAC, ABET, and NIRF accreditation and other ranking frameworks for the betterment of organizational standards. His research interests include Biometrics, Digital Image Processing, Artificial Intelligence, Industry 5.0, and Computational Intelligence.

    Dr. Neha Sharma is an Assistant Professor in the Department of Computer Science and Engineering Department in Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India. She received her Ph.D. degree in Computer Science Engineering from GD Goenka University, Gurugram, Haryana, India, and has vast teaching experience of more than 12 Years in a reputed organization. She has more than 20 international publications in reputed peer-reviewed journals including IEEE Xplore. Her main area of research is Image processing, Machine learning, Deep Learning, and Cyber Security. She has also published several National and International Patents under the Intellectual Property Rights of the Government of India and abroad. Dr. Sharma is actively associated with NAAC preparations at the university interface and is associated with many high-impact societies like IEEE (Senior Member), ACM, and ISTE (lifetime Member).

    Dr. Ahmed A. Elngar is an Associate Professor and Head of the Computer Science Department at the Faculty of Computers and Artificial Intelligence, Beni-Suef University, Egypt. He is also, an Associate Professor of Computer Science at the College of Computer Information Technology, American University in the Emirates, United Arab Emirates. Also, Dr. Elngar is an Adjunct Professor at the School of Technology, Woxsen University, India, and the Founder and Head of the Scientific Innovation Research Group (SIRG). He is a Director of the Technological and Informatics Studies Center (TISC), Faculty of Computers and Artificial Intelligence, Beni-Suef University. Dr. Elngar has more than 106 scientific research papers published in prestigious international journals and over 25 books covering such diverse topics as data mining, intelligent systems, social networks, and smart environments. He is a collaborative researcher and a member of the Egyptian Mathematical Society (EMS) and the International Rough Set Society (IRSS). His other research areas include the Internet of Things (IoT), Network Security, Intrusion Detection, Machine Learning, Data Mining, Artificial Intelligence, Big Data, Authentication, Cryptology, Healthcare Systems, and Automation Systems. Dr. Elngar is an Editor and Reviewer of many international journals around the world and has won several awards including the “Young Researcher in Computer Science Engineering,” from Global Outreach Education Summit and Awards 2019, in Delhi, India. Also, he was awarded the “Best Young Researcher Award (Male) (Below 40 years)”, Global Education and Corporate Leadership Awards 2018.

    Dr. Prasenjit Chatterjee is currently a Professor of Mechanical Engineering and Dean (Research and Consultancy) at MCKV Institute of Engineering (Autonomous), West Bengal, India. He has over 5400 citations and 120 research papers in various international journals and peer-reviewed conferences. He has authored and edited more than 33 books on intelligent decision-making, fuzzy computing, supply chain management, optimization techniques, risk management, and sustainability modeling. Dr. Chatterjee has received numerous awards including Best Track Paper Award, Outstanding Reviewer Award, Best Paper Award, Outstanding Researcher Award, and University Gold Medal. Dr. Chatterjee has been the Guest Editor of several special issues in different SCIE, Scopus, ESCI (Clarivate Analytics) indexed journals. He is the Lead Series Editor of a few book series and is one of the developers of two multiple-criteria decision-making methods called Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI).

    Dr. P Naga Srinivasu is an Associate Professor in the Computer Science and Engineering Department at Prasad V. Potluri Siddhartha Institute of Technology, India. He obtained a bachelor’s degree in computer science engineering from SSIET, JNTU Kakinada (2011), and a master’s degree in computer science technology from GITAM University, Visakhapatnam (2013). He was awarded a doctoral degree by GITAM University for his thesis on Automatic Segmentation Methods for Volumetric Estimate of damaged Areas in Astrocytoma instances Identified from the 2D Brain MR Imaging. His fields of study include biomedical imaging, soft computing, explainable AI, and healthcare informatics. He has published numerous publications in reputable peer-reviewed journals and has edited book volumes with various publishers. He is also an active reviewer for more than 40 journals and has served as a guest editor and technical advisory board member for various international conferences.