Securing Industrial Control Systems: Advanced Strategies and Technologies

This book offers an in-depth exploration of industrial control systems (ICS), examining their evolution, architecture, and security challenges. ICS plays a pivotal role in automating industrial operations, from manufacturing to utilities, and its components range from sensors and controllers to communication protocols. This book provides a comprehensive analysis of each aspect of ICS, including Supervisory Control and Data Acquisition (SCADA) systems, industrial automation, and field devices. The text dives deep into the importance of securing these systems to ensure operational efficiency, data integrity, and safety and includes additional code links.

Through detailed chapters, readers will gain insights into the latest trends, including the integration of IoT technologies, network communication protocols and attack vectors that threaten industrial systems. This book also focuses on practical security measures, such as intrusion detection, static defense strategies, and cyber resilience techniques, which are essential for protecting critical infrastructure. Case studies are provided to illustrate real-world applications and solutions that enhance the security and performance of ICS environments.

This book targets Industrial engineers, cybersecurity professionals, system architects, and researchers specializing in ICS and Supervisory Control Data Acquisition (SCADA) systems.  Graduate students in engineering and computer science, IT professionals working in critical infrastructure sectors, and industrial automation consultants will also find this book useful.

Dr. Mohammad Ashiqur Rahman is an Associate Professor at Florida International University (FIU) in the Department of Electrical and Computer Engineering. He leads the Analytics of Cyber Defense (ACyD) Lab at FIU and holds a secondary appointment in the Knight Foundation School of Computing and Information Sciences. Dr. Rahman earned his Ph.D. in Computing and Information Systems from the University of North Carolina at Charlotte. He has published extensively in the areas of cybersecurity and systems analysis. He is a senior member of IEEE and a member of ACM.

Dr. Syed Bahauddin Alam is an Assistant Professor of Nuclear, Plasma and Radiological Engineering at the University of Illinois Urbana-Champaign (UIUC). He leads the MARTIANS (Machine Learning & ARTficial Intelligence for Advancing Nuclear Systems) Lab. Dr. Alam has received several awards for his research and teaching, including the Outstanding Teaching Award from Missouri S&T in 2021 and the Most Exemplary Graduate Fellow Award on “Nuclear Nonproliferation Fellowship 2017” by KAIST. His notable achievements include the ANS Best Student Paper Award (ICAPP 2016), and he has been nominated for various awards including the Young Generation/Student Award (ICAPP 2017).

Dr. Kishor Datta Gupta (Senior Member, IEEE) received his Ph.D. from the University of Memphis. He is currently an Assistant Professor in the Cyber-Physical Department at Clark Atlanta University. His research interests include bio-inspired algorithms, computer security, and computer vision. He has one patent and several peer-reviewed publications related to adversarial machine learning and cybersecurity. He also serves as a Program Committee Member for the AAAI-23 Conference.

Dr. Roy George received his B.Sc. in electronics and telecommunication engineering from Kerala University, India, and his Ph.D. in computer science from Tulane University, New Orleans, LA, USA. He is currently a Professor and Chair of the Department of Cyber-Physical Systems at Clark Atlanta University. His expertise includes machine learning, cybersecurity, and network science. He has authored over 60 articles and a book on Data Modeling. Dr. George has directed multiple Research Centers of Excellence and has received funding from various U.S. Government agencies and private corporations. He was recognized as an Atlanta Top Technology Leader by the Atlanta Business Chronicle in 2015.

Sunzida Siddique is a researcher at Daffodil International University. Her research interests encompass Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), Computer Vision, Digital Twin technologies, and Cybersecurity. She earned her post-graduate degree from Jahangir Nagar University and completed her undergraduate studies at Daffodil International University. Sunzida has contributed to the field with several peer-reviewed publications, focusing on machine learning and cybersecurity.

Kazuma Kobayashi is a Ph.D. student at the University of Illinois Urbana-Champaign, specializing in Nuclear Engineering. His research focuses on digital twin enabling technologies, machine learning, and signal processing. Kazuma holds a Master of Science in Nuclear Engineering from Missouri University of Science and Technology and a Bachelor of Science in Physics from Rikkyo University. His work is recognized for its contributions to advancing technologies in nuclear systems and related fields.