Quantum Cryptography and Annealing for Securing Industrial IoT
- 1st Edition - February 27, 2026
- Latest edition
- Editors: Seifedine Kadry, Balamurugan Balusamy, S. B. Goyal, S. Sountharrajan, M. Karthiga, E. Suganya
- Language: English
Quantum Cryptography and Annealing for Securing Industrial IoT focuses on the rapidly evolving field of quantum security solutions for Industrial Internet of Things (IIoT) platfo… Read more
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Quantum Cryptography and Annealing for Securing Industrial IoT focuses on the rapidly evolving field of quantum security solutions for Industrial Internet of Things (IIoT) platforms, emphasizing the critical intersection of quantum cryptography, post-quantum cryptography, and their practical applications in IIoT. The book’s primary objective is to drive advancements that significantly intersect quantum cryptography in securing IIoT devices, elevate secure IIoT infrastructures, and optimize the overall delivery. Distinguishing itself by prioritizing practical applications, it offers a nuanced perspective on how technological integrations in quantum cryptosystems are actively employed in real-world scenarios.
The authors meticulously examine the role of quantum cryptosystems in the design, analysis, and optimization of IIoT-specific hardware, covering their resilience to physical and side-channel attacks and evaluating performance. This book strikes a balance between theoretical concepts and practical applications, providing insights into the challenges and solutions encountered in applying quantum cryptographical principles to IIoT engineering problems.
The authors meticulously examine the role of quantum cryptosystems in the design, analysis, and optimization of IIoT-specific hardware, covering their resilience to physical and side-channel attacks and evaluating performance. This book strikes a balance between theoretical concepts and practical applications, providing insights into the challenges and solutions encountered in applying quantum cryptographical principles to IIoT engineering problems.
- Presents clear, concise, and reader-friendly quantum cryptographical concepts through the use of accessible language, diagrams, and examples to enhance the learning experience
- Includes real-world examples and case studies, demonstrating the practical applications of quantum cryptographical concepts in the design and development of industrial robots and IIoT devices
- Caters to a diverse audience with backgrounds in mathematics, engineering, cybersecurity, quantum computing, and industrial engineering, making the content accessible to a broad range of readers
Information security professionals, cybercrime and digital forensic investigators, cyber response and remediation teams, forensic analysts, software developers, e-discovery researchers, security managers, computer science analysts, consultants, and researchers in academia and industry. This book will also be useful to professionals, researchers, academics, students and practitioners in the field of computer science and cybersecurity focused on Industrial IoT security and edge computing, specifically those involved in security-related aspects.
1. Introduction to Quantum Cryptography and Post-Quantum Cryptography for Securing IIoT Platforms
2. Design Considerations for IIoT Devices
3. Mathematical Modeling for Secure IIoT Optimization with Quantum-Inspired Techniques
4. Linear Algebra and Calculus for Industrial Robots and IIoT devices
5. Quantum Annealing for IIoT Optimisation and Security
6. Sensor Fusion and Data Processing for IIoT devices Control
7. Industrial Digital Twins for Enhanced Connectivity and Security
8. Motion Planning and Trajectory Optimization for Industrial IoT devices
9. Safety and Stability Analysis of Industrial IoT Systems
10. Quantum technologies for Enhanced Security in Manufacturing Systems
11. Industrial Quantum Computing applications
12. Deep learning and Quantum-inspired Techniques for Feature Extraction and Anomaly Detection in IIoT Environments
13. Quantum Cybersecurity in IIoT based Power grids
14. Practical Quantum Cryptosystems: Implementation Insights for IIoT Platforms
15. Computational Tools and Techniques for Industrial Engineering
16. Ethical Considerations of Industrial Robots and IIoT devices
2. Design Considerations for IIoT Devices
3. Mathematical Modeling for Secure IIoT Optimization with Quantum-Inspired Techniques
4. Linear Algebra and Calculus for Industrial Robots and IIoT devices
5. Quantum Annealing for IIoT Optimisation and Security
6. Sensor Fusion and Data Processing for IIoT devices Control
7. Industrial Digital Twins for Enhanced Connectivity and Security
8. Motion Planning and Trajectory Optimization for Industrial IoT devices
9. Safety and Stability Analysis of Industrial IoT Systems
10. Quantum technologies for Enhanced Security in Manufacturing Systems
11. Industrial Quantum Computing applications
12. Deep learning and Quantum-inspired Techniques for Feature Extraction and Anomaly Detection in IIoT Environments
13. Quantum Cybersecurity in IIoT based Power grids
14. Practical Quantum Cryptosystems: Implementation Insights for IIoT Platforms
15. Computational Tools and Techniques for Industrial Engineering
16. Ethical Considerations of Industrial Robots and IIoT devices
- Edition: 1
- Latest edition
- Published: February 27, 2026
- Language: English
SK
Seifedine Kadry
Seifedine Kadry is a Professor in the Department of Mathematics and Computer Science, at Norrof University College, in Norway. He has a Bachelor’s degree in 1999 from Lebanese University, MS degree in 2002 from Reims University (France) and EPFL (Lausanne), PhD in 2007 from Blaise Pascal University (France), HDR degree in 2017 from Rouen University. At present, his research focuses on data Science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing, and ABET program evaluator for Engineering Tech. He is a Fellow of IET, Fellow of IETE, and Fellow of IACSIT. He is a distinguished speaker of IEEE Computer Society.
Affiliations and expertise
Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon; Department of Applied Data Science, Noroff University College, Kristiansand, NorwayBB
Balamurugan Balusamy
Balamurugan Balusamy is Associate Dean Student in Shiv Nadar University, Delhi-NCR. Prior to this assignment he was Professor, School of Computing Sciences & Engineering and Director International Relations at Galgotias University, Greater Noida, India. His contributions focus on Engineering Education, Block chain and Data Sciences. His Academic degrees and twelve years of experience working as a faculty in a global University like VIT University, Vellore has made him more receptive and prominent in his domain. He does have 200 plus high impact factor papers in Springer, Elsevier and IEEE. He has done more than 80 Edited and authored books and collaborated with eminent professors across the world from top QS ranked university. Prof. Balamurugan Balusamy has served up to the position of Associate Professor in his stint of 12 years of experience with VIT University, Vellore. He had completed his Bachelors, Masters and PhD Degrees from Top premier institutions from India. His passion is teaching and adapts different design thinking principles while delivering his lectures. He has published 80+ books on various technologies and visited 15 plus countries for his technical course. He has several top-notch conferences in his resume and has published over 200 of quality journal, conference and book chapters combined. He serves in the advisory committee for several start-ups and forums and does consultancy work for industry on Industrial IOT. He has given over 195 talks in various events and symposium.
Affiliations and expertise
Shiv Nadar University, Delhi-NCR Campus, IndiaSG
S. B. Goyal
Dr. S. B. Goyal received his Ph.D. in Computer Science and Engineering from Banasthali University, Rajasthan, India, in 2012. He is currently working as Professor and Dean–CSE at Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India. He has over 22 years of national and international academic and research experience and has contributed to integrating Industry 4.0 technologies, including blockchain and artificial intelligence, into academic curricula.
Dr. Goyal holds more than ten international patents and copyrights from Australia, Germany, and India. His research interests include blockchain, artificial intelligence, cloud computing, cybersecurity, the Internet of Things, and data mining. He has served as editor or co-editor for several academic books and as a reviewer or guest editor for journals published by IEEE, Inderscience, IGI Global, and Springer. He has also been an invited speaker at international events such as Bloconomic 2019 and the World AI Show 2021.
Affiliations and expertise
Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, IndiaSS
S. Sountharrajan
S. Sountharrajan completed his PhD from Anna University in Information and Communication Engineering in the year 2017 and is currently working as Associate Professor in the School of Computing (SOC) at Amrita Vishwa Vidyapeetham, Chennai Campus. He is Program Head, B. Tech Computer Science and Engineering. He was sanctioned an amount of Rs. 38,00,000 from the funding agencies like DST, AICTE and ICMR. He has also published papers in 10 International / 6 National Conferences. He was published 35 International journals including 50 Scopus index and 12 SCI. He has been certified from reputed companies of India like the IBM, DELL EMC Corporation. He has delivered 33 Guest Lectures in reputed universities and Institutions in India. He has worked on Big Data, cloud computing show the importance of cloud deployed applications.
Affiliations and expertise
Department of Computer Science and Engineering , School of Computing, Amrita Vishwa Vidyapeetham, Chennai, IndiaMK
M. Karthiga
Dr. M. Karthiga is currently working as an Associate Professor in the Department of Computer science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, India. She holds more than 11 years of professional experience. She is presently working in Machine Learning and Deep Learning Projects. She is involved in Data Science Lab. She published 28 articles in leading National and International journals. She is a reviewer in reputed journals like Knowledge based Systems, Signals, Image and Video Processing, Future Generation Computer Systems, MDPI journals and etc., She published more than 11 book chapters in leading books of Elsevier and Springer. She is an active researcher in the field of Machine learning and Data Analytics. Also, her research interest includes Data mining, Image Mining, Internet of Things, Artificial Intelligence and Deep Learning. She has received 5 patent grants and filed more than 13 National level Patents under Machine Learning and Internet of Things. She is a Lifetime member of ISTE professional society.
Affiliations and expertise
Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, IndiaES
E. Suganya
E. Suganya is an Assistant Professor the Department of Information Technology in Sri SivasubramaniyaNadar College of Engineering, Chennai. She has over 4 years of teaching experience and 3 year of Research experience. She received her B.Tech (IT) degree from B.S.A Crescent Engineering College, Chennai M.E. in Computer Science and Engineering from Anna University, Chennai and Ph.D. from Anna University, Chennai in the area of Data Analytics and Optimization. Her current research areas of interest include Data Analytics, Data mining, Optimization Algorithm. she has published more than 20 papers in International and National Journals and Conferences. One of her papers has been awarded “Best paper award” at IEEE international conference. She is a Lifetime member of ISTE professional society.
Affiliations and expertise
Department of Information Technology, Sri Sivasubramaniya Nadar College of Engineering, IndiaRead Quantum Cryptography and Annealing for Securing Industrial IoT on ScienceDirect