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Compressed Sensing for Privacy-Preserving Data Processing -  Tiziano Bianchi,  Enrico Magli,  Matteo Testa,  Diego Valsesia

Compressed Sensing for Privacy-Preserving Data Processing (eBook)

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2018 | 1st ed. 2019
VIII, 91 Seiten
Springer Singapore (Verlag)
978-981-13-2279-2 (ISBN)
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The objective of this book is to provide the reader with a comprehensive survey of the topic compressed sensing in information retrieval and signal detection with privacy preserving functionality without compromising the performance of the embedding in terms of accuracy or computational efficiency. The reader is guided in exploring the topic by first establishing a shared knowledge about compressed sensing and how it is used nowadays. Then, clear models and definitions for its use as a cryptosystem and a privacy-preserving embedding are laid down, before tackling state-of-the-art results for both applications. The reader will conclude the book having learned that the current results in terms of security of compressed techniques allow it to be a very promising solution to many practical problems of interest. The book caters to a broad audience among researchers, scientists, or engineers with very diverse backgrounds, having interests in security, cryptography and privacy in information retrieval systems. Accompanying software is made available on the authors' website to reproduce the experiments and techniques presented in the book. The only background required to the reader is a good knowledge of linear algebra, probability and information theory.

The objective of this book is to provide the reader with a comprehensive survey of the topic compressed sensing in information retrieval and signal detection with privacy preserving functionality without compromising the performance of the embedding in terms of accuracy or computational efficiency. The reader is guided in exploring the topic by first establishing a shared knowledge about compressed sensing and how it is used nowadays. Then, clear models and definitions for its use as a cryptosystem and a privacy-preserving embedding are laid down, before tackling state-of-the-art results for both applications. The reader will conclude the book having learned that the current results in terms of security of compressed techniques allow it to be a very promising solution to many practical problems of interest. The book caters to a broad audience among researchers, scientists, or engineers with very diverse backgrounds, having interests in security, cryptography and privacy in informationretrieval systems. Accompanying software is made available on the authors' website to reproduce the experiments and techniques presented in the book. The only background required to the reader is a good knowledge of linear algebra, probability and information theory.

Introduction.- Compressed Sensing and Security.- Compressed Sensing as a Cryptosystem.- Privacy-preserving Embeddings.- Conclusion.

Erscheint lt. Verlag 1.9.2018
Reihe/Serie SpringerBriefs in Electrical and Computer Engineering
SpringerBriefs in Electrical and Computer Engineering
SpringerBriefs in Signal Processing
SpringerBriefs in Signal Processing
SpringerBriefs in Signal Processing
Zusatzinfo VIII, 91 p. 29 illus., 26 illus. in color.
Verlagsort Singapore
Sprache englisch
Themenwelt Informatik Netzwerke Sicherheit / Firewall
Informatik Theorie / Studium Algorithmen
Mathematik / Informatik Informatik Web / Internet
Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Finanz- / Wirtschaftsmathematik
Naturwissenschaften
Technik Elektrotechnik / Energietechnik
Schlagworte circulant matrices • compressed sensing • cryptosystem models • data privacy • Data Security • dimensionality reduction • energy abfuscation • internet-of-things • privacy preserving information retrieval • random matrices • Random Matrix Theory • signal embedding
ISBN-10 981-13-2279-1 / 9811322791
ISBN-13 978-981-13-2279-2 / 9789811322792
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