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Machine Learning in Cyber Trust

Security, Privacy, and Reliability

By Jeffrey J. P. Tsai , Philip S. Yu

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In cyber-based systems, tasks can be formulated as learning problems and approached as machine-learning algorithms. This book covers applications of machine-learning methods in reliability, security, performance and privacy issues in cyber space.

Full Description

  • ISBN13: 978-0-3878-8734-0
  • 378 Pages
  • User Level: Science
  • Publication Date: April 5, 2009
  • Available eBook Formats: PDF
  • eBook Price: $129.00
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Full Description
Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms. This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover what types of learning methods are at their disposal, summarizing the state-of-the-practice in this significant area, and giving a classification of existing work. Those working in the field of cyber-based systems, including industrial managers, researchers, engineers, and graduate and senior undergraduate students will find this an indispensable guide in creating systems resistant to and tolerant of cyber attacks.
Table of Contents

Table of Contents

  1. Introduction.
  2. Cyber terrorism.
  3. Machine learning.
  4. Security.
  5. Reliability.
  6. Privacy.
  7. Intrusion detection.
  8. Web security.
  9. Conclusion.
  10. Reference.
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