Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis
Rokka Chhetri, Sujit, Al Faruque, Mohammad Abdullah
Produktnummer:
18bc7b187c878949c49889eb4b6f4312b9
| Autor: | Al Faruque, Mohammad Abdullah Rokka Chhetri, Sujit |
|---|---|
| Themengebiete: | Design Automation of Cyber-Physical Systems IoT-enabled Living Digital Twin Modeling Security of Cyber-Physical Systems machine learning for security in CPS stochastic phenomena affecting CPS |
| Veröffentlichungsdatum: | 09.02.2020 |
| EAN: | 9783030379612 |
| Sprache: | Englisch |
| Seitenzahl: | 235 |
| Produktart: | Gebunden |
| Verlag: | Springer International Publishing |
Produktinformationen "Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis"
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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