Secure networked inference with unreliable data sources /
General Material Designation
[Book]
First Statement of Responsibility
Aditya Vempaty, Bhavya Kailkhura, Pramod K. Varshney.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Singapore :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
2018.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references.
CONTENTS NOTE
Text of Note
Intro; Preface; Acknowledgements; Contents; 1 Introduction; 1.1 Distributed Inference Networks; 1.2 Motivation: Byzantine Generals' Problem; 1.3 Distributed Inference in the Presence of Byzantines: Two Viewpoints; 1.3.1 Analysis from the Attacker's Perspective; 1.3.2 Analysis from the Network Designer's Perspective; 1.4 Outline; References; 2 Background; 2.1 Foundational Concepts of Inference; 2.1.1 Binary Hypothesis Testing; 2.1.2 M-Ary Hypothesis Testing; 2.1.3 Parameter Estimation; 2.1.4 Asymptotic Performance Metrics; 2.2 Distributed Inference; 2.2.1 Network Topologies.
Text of Note
2.2.2 Practical Concerns2.3 Taxonomy of Results; 2.3.1 Fundamental Limits; 2.3.2 Mitigation Schemes; References; 3 Distributed Detection with Unreliable Data Sources; 3.1 Distributed Bayesian Detection with Byzantines: Parallel Networks; 3.1.1 System Model; 3.1.2 Analysis from Attacker's Perspective; 3.1.3 Analysis from Network Designer's Perspective; 3.2 Distributed Neyman-Pearson Detection with Byzantine Data: Parallel Networks; 3.2.1 System Model; 3.2.2 Analysis from Attacker's Perspective; 3.2.3 Analysis from Network Designer's Perspective; 3.2.4 Covert Byzantine Attacks.
Text of Note
3.3 Distributed Detection with Unlabeled Byzantine Data: Multi-hop Networks3.3.1 System Model; 3.3.2 Analysis from Attacker's Perspective; 3.3.3 Analysis from Network Designer's Perspective; 3.4 Distributed Detection with Labeled Byzantine Data: Multi-hop Networks; 3.4.1 System Model; 3.4.2 Analysis from Attacker's Perspective; 3.4.3 Analysis from Network Designer's Perspective; 3.5 Distributed Detection with Byzantine Data: Peer-to-Peer Networks; 3.5.1 System Model; 3.5.2 Analysis from Attacker's Perspective; 3.5.3 Analysis from Network Designer's Perspective; 3.6 Summary; References.
Text of Note
4 Distributed Estimation and Target Localization4.1 Target Localization with Byzantine Data: Parallel Networks; 4.1.1 System Model; 4.1.2 Analysis from Attacker's Perspective; 4.1.3 Analysis from Network Designer's Perspective; 4.2 Distributed Parameter Estimation with Multiple Attack Strategies: Parallel Networks; 4.2.1 System Model; 4.2.2 Identification and Categorization of Sensors; 4.2.3 Joint Estimation Including Attack Parameters; 4.3 Distributed Parameter Estimation with Adversaries: Peer-to-Peer Networks; 4.3.1 System Model; 4.3.2 Analysis from Network Designer's Perspective.
Text of Note
4.4 SummaryReferences; 5 Some Additional Topics on Distributed Inference; 5.1 Distributed Inference with M-ary Quantized Byzantine Data; 5.1.1 System Model; 5.1.2 Analysis from Attacker's Perspective; 5.2 Target Tracking with Quantized Byzantine Data; 5.2.1 System Model; 5.2.2 Analysis from Attacker's Perspective; 5.2.3 Analysis from Network Designer's Perspective; 5.3 Summary; References; 6 Distributed Inference with Unreliable Data: Some Unconventional Directions; 6.1 Friendly Byzantines to Improve Secrecy; 6.1.1 Collaborative Compressive Detection.
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SUMMARY OR ABSTRACT
Text of Note
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.
ACQUISITION INFORMATION NOTE
Source for Acquisition/Subscription Address
Springer Nature
Stock Number
com.springer.onix.9789811323126
OTHER EDITION IN ANOTHER MEDIUM
Title
Secure networked inference with unreliable data sources.
International Standard Book Number
9789811323119
TOPICAL NAME USED AS SUBJECT
Computer network architectures.
Electronic data processing-- Distributed processing.
Coding theory & cryptology.
Communications engineering-- telecommunications.
Computer network architectures.
Computer security.
COMPUTERS-- Computer Literacy.
COMPUTERS-- Computer Science.
COMPUTERS-- Data Processing.
COMPUTERS-- Hardware-- General.
COMPUTERS-- Information Technology.
COMPUTERS-- Machine Theory.
COMPUTERS-- Reference.
Electronic data processing-- Distributed processing.