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Secure networked inference with unreliable data sources

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Secure networked inference with unreliable data sources/ by Aditya Vempaty, Bhavya Kailkhura, Pramod K. Varshney.
Author:	Vempaty, Aditya.
other author:	Kailkhura, Bhavya.
Published:	Singapore :Springer Singapore : : 2018.,
Description:	xiii, 208 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Computer network architectures. -
Online resource:	https://doi.org/10.1007/978-981-13-2312-6
ISBN:	9789811323126

Secure networked inference with unreliable data sources
Vempaty, Aditya.

Secure networked inference with unreliable data sources[electronic resource] /by Aditya Vempaty, Bhavya Kailkhura, Pramod K. Varshney. - Singapore :Springer Singapore :2018. - xiii, 208 p. :ill., digital ;24 cm.

Chapter 1 Introduction -- Chapter 2 Conventional Inference theories -- Chapter 3 Distributed Detection in Networks -- Chapter 4 Distributed Estimation and Target Localization -- Chapter 5 Distributed Classification and Target Tracking -- Chapter 6 New Research Directions Discussion and conclusions.

The book presents theory and algorithms for secure networked inference in the presence of Byzantines. It derives fundamental limits of networked inference in the presence of Byzantine data and designs robust strategies to ensure reliable performance for several practical network architectures. In particular, it addresses inference (or learning) processes such as detection, estimation or classification, and parallel, hierarchical, and fully decentralized (peer-to-peer) system architectures. Furthermore, it discusses a number of new directions and heuristics to tackle the problem of design complexity in these practical network architectures for inference.

ISBN: 9789811323126

Standard No.: 10.1007/978-981-13-2312-6doiSubjects--Topical Terms:

565372
Computer network architectures.

LC Class. No.: TK5105.5

Dewey Class. No.: 004.65

Secure networked inference with unreliable data sources
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505 0 $a Chapter 1 Introduction -- Chapter 2 Conventional Inference theories -- Chapter 3 Distributed Detection in Networks -- Chapter 4 Distributed Estimation and Target Localization -- Chapter 5 Distributed Classification and Target Tracking -- Chapter 6 New Research Directions Discussion and conclusions.
520 $a The book presents theory and algorithms for secure networked inference in the presence of Byzantines. It derives fundamental limits of networked inference in the presence of Byzantine data and designs robust strategies to ensure reliable performance for several practical network architectures. In particular, it addresses inference (or learning) processes such as detection, estimation or classification, and parallel, hierarchical, and fully decentralized (peer-to-peer) system architectures. Furthermore, it discusses a number of new directions and heuristics to tackle the problem of design complexity in these practical network architectures for inference.
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