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Machine Learning in Cyber Trust

Overview of attention for book
Cover of 'Machine Learning in Cyber Trust'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Cyber-Physical Systems: A New Frontier
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    Chapter 2 Misleading Learners: Co-opting Your Spam Filter
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    Chapter 3 Survey of Machine Learning Methods for Database Security
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    Chapter 4 Identifying Threats Using Graph-based Anomaly Detection
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    Chapter 5 On the Performance of Online Learning Methods for Detecting Malicious Executables
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    Chapter 6 Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems
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    Chapter 7 A Non-Intrusive Approach to Enhance Legacy Embedded Control Systems with Cyber Protection Features
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    Chapter 8 Image Encryption and Chaotic Cellular Neural Network
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    Chapter 9 From Data Privacy to Location Privacy
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    Chapter 10 Privacy Preserving Nearest Neighbor Search
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    Chapter 11 High-Confidence Compositional Reliability Assessment of SOA-Based Systems Using Machine Learning Techniques
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    Chapter 12 Model, Properties, and Applications of Context-Aware Web Services
Attention for Chapter 11: High-Confidence Compositional Reliability Assessment of SOA-Based Systems Using Machine Learning Techniques
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Citations

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Readers on

mendeley
6 Mendeley
Summary Dimensions citations
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Chapter title
High-Confidence Compositional Reliability Assessment of SOA-Based Systems Using Machine Learning Techniques
Chapter number 11
Book title
Machine Learning in Cyber Trust
Published in
ADS, January 2009
DOI 10.1007/978-0-387-88735-7_11
Book ISBNs
978-0-387-88734-0, 978-0-387-88735-7
Authors

Venkata U. B. Challagulla, Farokh B. Bastani, I-Ling Yen

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 17%
Unknown 5 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 50%
Student > Postgraduate 2 33%
Student > Master 1 17%
Readers by discipline Count As %
Computer Science 4 67%
Engineering 2 33%

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