Fuchun Guo's Books

Introduction to Security Reduction

By: Fuchun Guo,Willy Susilo,Yi Mu

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Introduction to Security Reduction

By: Fuchun Guo,Willy Susilo,Yi Mu

This monograph illustrates important notions in security reductions and essential techniques in security reductions for group-based cryptosystems. Using digital signatures and encryption as examples, the authors explain how to program correct security reductions for those cryptographic primitives. Various schemes are selected and re-proven in this book to demonstrate and exemplify correct security reductions. This book is suitable for researchers and graduate students engaged with public-key cryptography.

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Page Count

262

Publisher

Springer

Published Date

ISBN 10

3319930494

ISBN 13

9783319930497

Analysis and Design of Networked Control Systems under Attacks

By: Yuan Yuan,Hongjiu Yang,Lei Guo,Fuchun Sun

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Analysis and Design of Networked Control Systems under Attacks

By: Yuan Yuan,Hongjiu Yang,Lei Guo,Fuchun Sun

This book adopts a systematic view of the control systems in cyber-physical systems including the security control of the optimal control system, security control of the non-cooperative game system, quantify the impact of the Denial-of-Service attacks on the optimal control system, and the adaptive security control of the networked control systems. Because the cyber-physical system is a hybrid system, it adopts cross layer approach to handle the security control of the CPS. It presents a number of attack models according to the attack scenario and defense facilities, and a number of cross-layer co-design methodologies to secure the control of CPS.

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Page Count

278

Publisher

CRC Press

Published Date

ISBN 10

0429812280

ISBN 13

9780429812286

Wearable Technology for Robotic Manipulation and Learning

By: Bin Fang,Fuchun Sun,Huaping Liu,Chunfang Liu,Di Guo

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Wearable Technology for Robotic Manipulation and Learning

By: Bin Fang,Fuchun Sun,Huaping Liu,Chunfang Liu,Di Guo

Over the next few decades, millions of people, with varying backgrounds and levels of technical expertise, will have to effectively interact with robotic technologies on a daily basis. This means it will have to be possible to modify robot behavior without explicitly writing code, but instead via a small number of wearable devices or visual demonstrations. At the same time, robots will need to infer and predict humans’ intentions and internal objectives on the basis of past interactions in order to provide assistance before it is explicitly requested; this is the basis of imitation learning for robotics. This book introduces readers to robotic imitation learning based on human demonstration with wearable devices. It presents an advanced calibration method for wearable sensors and fusion approaches under the Kalman filter framework, as well as a novel wearable device for capturing gestures and other motions. Furthermore it describes the wearable-device-based and vision-based imitation learning method for robotic manipulation, making it a valuable reference guide for graduate students with a basic knowledge of machine learning, and for researchers interested in wearable computing and robotic learning.

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Page Count

219

Publisher

Springer Nature

Published Date

ISBN 10

9811551243

ISBN 13

9789811551246

Robotic Tactile Perception and Understanding

A Sparse Coding Method

By: Huaping Liu,Fuchun Sun

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Robotic Tactile Perception and Understanding

A Sparse Coding Method

By: Huaping Liu,Fuchun Sun

This book introduces the challenges of robotic tactile perception and task understanding, and describes an advanced approach based on machine learning and sparse coding techniques. Further, a set of structured sparse coding models is developed to address the issues of dynamic tactile sensing. The book then proves that the proposed framework is effective in solving the problems of multi-finger tactile object recognition, multi-label tactile adjective recognition and multi-category material analysis, which are all challenging practical problems in the fields of robotics and automation. The proposed sparse coding model can be used to tackle the challenging visual-tactile fusion recognition problem, and the book develops a series of efficient optimization algorithms to implement the model. It is suitable as a reference book for graduate students with a basic knowledge of machine learning as well as professional researchers interested in robotic tactile perception and understanding, and machine learning.

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