Data Driven Modeling Of Cyber Physical Systems Using Side Channel Analysis
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Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis
Author: Sujit Rokka Chhetri
language: en
Publisher: Springer Nature
Release Date: 2020-02-08
This book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS.
Smarter Cyber Physical Systems
Cyber-Physical Systems (CPS) is featured by the tight integration of cyber and physical components. CPS has made major advances with a broad societal impact. Now in the era of Industry Revolution 4.0, CPS is considered as an enabling technology. Combined with autonomy, big data, machine learning and internet of things, CPS empowers systems with greater intelligence to address uncertainties, unknowns, attacks, and unexpected events. This book highlights the latest advances and explores the new trends in the design and implementation of smarter Cyber-Physical systems (CPS). It introduces integrated model-based and data-driven solutions for CPS that demonstrate features including both adaptability and interpretability. Key topics covered include reinforcement learning, digital twin and large-scale networks. The book then presents the latest codesign techniques that address practical computation, networking, control, and physical constraints. It examines important issues related to human CPS, safety, resilience and privacy. The chapters feature the tight integration of theory and practice, including problems motivated from applications, fundamental research development that are generally applicable, and implementation in real system applications. A wide range of CPS applications are covered, including robotics, autonomous driving, unmanned aerial vehicles and smart cities.
Digital Twins
This is the second of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book focuses on the application of digital twins in various contexts, e.g. computer-aided experimental design, seed train prediction, and lifeline analysis. Covering fundamentals as well as applications, the two volumes offers the ideal introduction to the topic for researchers in academy and industry alike.