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Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis
eBook
eBook
Fachbuch
2020

Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis

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ISBN
EAN
978-3-030-37962-9
9783030379629
Artikel-Nr.
6NLKPE8
Rabatt
-21.7
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CHF 94.50
CHF
73.95
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1
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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.

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Stichwörter
Inhaltsverzeichnis
1. Introduction2. Data-Driven Attack Modeling using Acoustic Side-Channel3. Aiding Data-Driven Attack Model with a Compiler Modification4. Data-Driven Defense through Leakage Minimization5. Data-Driven Kinetic-Cyber Attack Detection6. Data-Driven Security Analysis using Generative Adversarial Networks7. Dynamic Data-Driven Digital Twin Modeling8. IoT-enabled Living Digital Twin Modeling9. Non-Euclidean Data-Driven Modeling using Graph Covolutional10. Dynamic Graph Graph Embedding
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Autoren/Autorinnen
Publikation
Schweiz
08.02.2020
Springer Verlag
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Sprache
Englisch
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eBook
PDF
235 Seiten
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