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

Sujit Rokka Chhetri, Mohammad Abdullah Al Faruque (Autoren)

Buch | Hardcover

XVI, 235 Seiten

2020
Springer International Publishing (Verlag)
9783030379612 (ISBN)

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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.

Sujit Rokka Chhetri is a recent graduate from the University of California, Irvine. He finished his Ph.D. in Computer Engineering from the Henry Samueli School of Engineering, where he was working as a graduate student researcher at Advanced Cyber-Physical Systems lab under the supervision of Prof. Mohammad Abdullah Al Faruque. He is currently a Staff Data Scientist at Palo Alto Networks. His research interest lies in data-driven modeling of cyber-physical systems. More specifically, his research focus is on analyzing the various source of analog emissions for potential side-channels. He is also interested in non-Euclidean data-driven modeling techniques including graph convolutional neural networks and knowledge graph embedding algorithms. Furthermore, his research also focusses on data-driven modeling techniques for building a digital twin of the cyber-physical systems. He has several publications in the top conferences and also holds one US patent. He received NDSS distinguished Poster award in 2016 as well.

1. Introduction.- 2. Data-Driven Attack Modeling using Acoustic Side-Channel.-3. Aiding Data-Driven Attack Model with a Compiler Modification.-4. Data-Driven Defense through Leakage Minimization.-5. Data-Driven Kinetic-Cyber Attack Detection.-6. Data-Driven Security Analysis using Generative Adversarial Networks.-7. Dynamic Data-Driven Digital Twin Modeling.-8. IoT-enabled Living Digital Twin Modeling.-9. Non-Euclidean Data-Driven Modeling using Graph Covolutional.-10. Dynamic Graph Graph Embedding.

Erscheinungsdatum	18.02.2020
Zusatzinfo	XVI, 235 p. 111 illus., 106 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	547 g
Themenwelt	Mathematik / Informatik ► Informatik ► Theorie / Studium
Themenwelt	Technik ► Elektrotechnik / Energietechnik
Schlagworte	Design Automation of Cyber-Physical Systems • IoT-enabled Living Digital Twin Modeling • machine learning for security in CPS • security of cyber-physical systems • stochastic phenomena affecting CPS
ISBN-13	9783030379612 / 9783030379612
Zustand	Neuware