
Compressed Sensing for Privacy-Preserving Data Processing
Springer (Publisher)
Published on 11. September 2018
Book
Paperback/Softback
VIII, 91 pages
978-981-13-2278-5 (ISBN)
Description
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.
More details
Series
Edition
2019 ed.
Language
English
Place of publication
Singapore
Singapore
Target group
Professional and scholarly
Illustrations
3 s/w Abbildungen, 26 farbige Abbildungen
VIII, 91 p. 29 illus., 26 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 6 mm
Weight
166 gr
ISBN-13
978-981-13-2278-5 (9789811322785)
DOI
10.1007/978-981-13-2279-2
Schweitzer Classification
Other editions
Additional editions

Matteo Testa | Diego Valsesia | Tiziano Bianchi
Compressed Sensing for Privacy-Preserving Data Processing
E-Book
09/2018
1st Edition
Springer
€53.49
Available for download
Content
Introduction.- Compressed Sensing and Security.- Compressed Sensing as a Cryptosystem.- Privacy-preserving Embeddings.- Conclusion.