Description

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

Trade Review

From the reviews:

"This is a useful book on machine learning for cyber security applications. It will be helpful to researchers and graduate students who are looking for an introduction to a specific topic in the field. All of the topics covered are well researched. The book consists of 12 chapters, grouped into four parts." (Imad H. Elhajj, ACM Computing Reviews, October, 2009)



Table of Contents
Cyber System.- Cyber-Physical Systems: A New Frontier.- Security.- Misleading Learners: Co-opting Your Spam Filter.- Survey of Machine Learning Methods for Database Security.- Identifying Threats Using Graph-based Anomaly Detection.- On the Performance of Online Learning Methods for Detecting Malicious Executables.- Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems.- A Non-Intrusive Approach to Enhance Legacy Embedded Control Systems with Cyber Protection Features.- Image Encryption and Chaotic Cellular Neural Network.- Privacy.- From Data Privacy to Location Privacy.- Privacy Preserving Nearest Neighbor Search.- Reliability.- High-Confidence Compositional Reliability Assessment of SOA-Based Systems Using Machine Learning Techniques.- Model, Properties, and Applications of Context-Aware Web Services.

Machine Learning in Cyber Trust

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    £125.99

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    RRP £139.99 – you save £14.00 (10%)

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    A Hardback by Jeffrey J. P. Tsai, Philip S. Yu

    1 in stock

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      Publisher: Springer-Verlag New York Inc.
      Publication Date: 28/04/2009
      ISBN13: 9780387887340, 978-0387887340
      ISBN10: 0387887342

      Description

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

      Trade Review

      From the reviews:

      "This is a useful book on machine learning for cyber security applications. It will be helpful to researchers and graduate students who are looking for an introduction to a specific topic in the field. All of the topics covered are well researched. The book consists of 12 chapters, grouped into four parts." (Imad H. Elhajj, ACM Computing Reviews, October, 2009)



      Table of Contents
      Cyber System.- Cyber-Physical Systems: A New Frontier.- Security.- Misleading Learners: Co-opting Your Spam Filter.- Survey of Machine Learning Methods for Database Security.- Identifying Threats Using Graph-based Anomaly Detection.- On the Performance of Online Learning Methods for Detecting Malicious Executables.- Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems.- A Non-Intrusive Approach to Enhance Legacy Embedded Control Systems with Cyber Protection Features.- Image Encryption and Chaotic Cellular Neural Network.- Privacy.- From Data Privacy to Location Privacy.- Privacy Preserving Nearest Neighbor Search.- Reliability.- High-Confidence Compositional Reliability Assessment of SOA-Based Systems Using Machine Learning Techniques.- Model, Properties, and Applications of Context-Aware Web Services.

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