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How secure are intelligent computing networks (ICNs) when data, algorithms, and computing power intertwine? As ICNs become the backbone of modern digital ecosystems, their growing complexity introduces unprecedented risks in security and safety. Integrated Security and Safety of Intelligent Computing Networks offers a groundbreaking, coupling-aware perspective that redefines how we understand and fortify ICN infrastructures.
This book goes beyond conventional security frameworks by examining the intricate, dynamic relationships among the three pillars of ICNs-data, computing power, and algorithms. It provides a systematic exploration of how their deep coupling can both empower and endanger these systems. Through a well-structured progression from foundational theories to real-world case studies, it uncovers the limitations of current defenses and introduces innovative, scenario-driven methodologies that address distributed attacks, data poisoning, and algorithmic vulnerabilities. From edge computing threats to federated learning backdoors, the book bridges theoretical modeling with practical solutions across system, data, and algorithm planes.
Designed for researchers, engineers, and graduate students specializing in cybersecurity, intelligent systems, and next-generation computing, this monograph delivers essential insights and tools to build trustworthy ICNs. With a strong focus on coupling-aware design and integrated defense strategies, it provides not only technical depth but also strategic foresight-empowering readers to navigate and shape the future of secure intelligent infrastructures.
List of contents
"Intelligent Computing Networks".- "Emerging Multi-Dimensional Integration of Security and Safety".- "The Projection onto System Plane".- "The Projection onto Data Plane".- "The Projection onto Algorithm Plane".- "The Platform of Integrated Security and Safety".
About the author
Cheng Wang is a Professor at the School of Computer Science and Technology, Tongji University, specializing in intelligent computing systems and networked infrastructures. He has published over 150 academic papers, in addition to 34 granted invention patents and leadership in prominent national initiatives, such as the National Key Research and Development Program of the Ministry of Science and Technology and the Industrial Internet Innovation and Development Engineering Program of the Ministry of Industry and Information Technology. He earned the National Science and Technology Progress Award and the Outstanding Ph.D. Dissertation Award from the China Computer Federation (CCF). He is also the author of three books published by Springer, namely Human Factor Security and Safety, Universal Behavior Computing for Security and Safety, and Computational Structural Behavior.
Hao Tang received his bachelor degree of engineering in the Department of Computer Science and Technology from Chongqing University of Posts and Telecommunications in June, 2020. He is currently pursuing the Ph.D. degree in the College of Computer Science and Technology at Tongji University in Shanghai, China. His research interests include privacy-preserving learning and distributed computing.
Summary
How secure are intelligent computing networks (ICNs) when data, algorithms, and computing power intertwine? As ICNs become the backbone of modern digital ecosystems, their growing complexity introduces unprecedented risks in security and safety.
Integrated Security and Safety of Intelligent Computing Networks
offers a groundbreaking, coupling-aware perspective that redefines how we understand and fortify ICN infrastructures.
This book goes beyond conventional security frameworks by examining the intricate, dynamic relationships among the three pillars of ICNs—data, computing power, and algorithms. It provides a systematic exploration of how their deep coupling can both empower and endanger these systems. Through a well-structured progression from foundational theories to real-world case studies, it uncovers the limitations of current defenses and introduces innovative, scenario-driven methodologies that address distributed attacks, data poisoning, and algorithmic vulnerabilities. From edge computing threats to federated learning backdoors, the book bridges theoretical modeling with practical solutions across system, data, and algorithm planes.
Designed for researchers, engineers, and graduate students specializing in cybersecurity, intelligent systems, and next-generation computing, this monograph delivers essential insights and tools to build trustworthy ICNs. With a strong focus on coupling-aware design and integrated defense strategies, it provides not only technical depth but also strategic foresight—empowering readers to navigate and shape the future of secure intelligent infrastructures.
