Atjaunināt sīkdatņu piekrišanu

E-grāmata: Compressed Sensing for Privacy-Preserving Data Processing

  • Formāts - EPUB+DRM
  • Cena: 53,52 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

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.
1 Introduction
1(6)
References 4(3)
2 Compressed Sensing and Security
7(18)
2.1 Compressed Sensing as a Cryptosystem
11(5)
2.1.1 Security Definitions
14(1)
2.1.2 Attack Scenarios
15(1)
2.2 Signal Embeddings
16(6)
References
22(3)
3 Compressed Sensing as a Cryptosystem
25(48)
3.1 Statistical Properties of Measurements
26(4)
3.2 Gaussian Sensing Matrices and Asymptotic Behavior
30(10)
3.2.1 Model Definition and Security Metrics
30(2)
3.2.2 Energy Obfuscation
32(2)
3.2.3 Upper Bound Validation
34(4)
3.2.4 Asymptotic Behavior
38(2)
3.3 Arbitrary Sensing Matrices
40(25)
3.3.1 Model Definition and Security Metrics
40(4)
3.3.2 Generic Unstructured Sensing Matrices
44(8)
3.3.3 Circulant Sensing Matrices
52(8)
3.3.4 Upper Bound Validation
60(5)
3.4 Practical Sensing
65(4)
3.4.1 Overview
65(1)
3.4.2 Sensing Matrix Classes
66(2)
3.4.3 Sensing Matrix Generation
68(1)
References
69(4)
4 Privacy-Preserving Embeddings
73(18)
4.1 User Authentication
74(9)
4.1.1 Overview
74(1)
4.1.2 System Description
75(6)
4.1.3 Security Analysis
81(2)
4.2 Bounded-Distance Clustering
83(6)
4.2.1 Overview
83(1)
4.2.2 Universal Embeddings
84(3)
4.2.3 Private Clustering
87(2)
References
89(2)
5 Conclusions
91