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Secure Networked Inference with Unreliable Data Sources / by Aditya Vempaty, Bhavya Kailkhura, Pramod K. Varshney

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: SpringerLink BücherPublisher: Singapore : Springer Singapore, 2018Description: Online-Ressource (XIII, 208 p. 74 illus., 71 illus. in color, online resource)ISBN:
  • 9789811323126
Subject(s): Additional physical formats: 9789811323119 | Printed edition: 9789811323119 DDC classification:
  • 004.6
LOC classification:
  • TK5105.5-5105.9
DOI: DOI: 10.1007/978-981-13-2312-6Online resources: Summary: 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 inferenceSummary: 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 conclusionsPPN: PPN: 1030106673Package identifier: Produktsigel: ZDB-2-SCS | ZDB-2-SEB | ZDB-2-SXCS
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