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Data Mining and Machine Learning in Cybersecurity

By: Material type: TextTextPublication details: Boca Raton : CRC Press, c2011.Description: 256 p. : 69 B/W illISBN:
  • 9780429063756
Subject(s): Genre/Form: Additional physical formats: No titleDDC classification:
  • 005.8 D812
Online resources: Available additional physical forms:
  • Also available in print edition.
Contents:
1. Introduction -- 2. Classical machine-learning paradigms for data mining -- 3. Supervised learning for misuse/signature detection -- 4. Machine learning for anomaly detection -- 5. Machine learning for hybrid detection -- 6. Machine learning for scan detection -- 7. Machine learning for profiling network traffic -- 8. Privacy-preserving data mining -- 9. Emerging challenges in cybersecurity.
Summary: Introducing basic concepts of machine learning and data mining methodologies for cyber security, this book provides a unified reference for specific machine learning solutions and cybersecurity problems. The authors focus on how to apply machine learning methodologies in cybersecurity, categorizing methods for detecting, scanning, profiling, intrusions, and anomalies. The text presents challenges and solutions in machine learning along with cybersecurity fundamentals. It also describes advanced problems in cybersecurity in the machine learning domain and examines privacy-preserving data mining methods as a proactive security solution-- Provided by publisher.
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Item type Current library Call number Status Barcode
E-Books E-Books Indian Institute of Technology Tirupati 005.8 D812 (Browse shelf(Opens below)) Available EB00418

An Auerbach book.

Includes bibliographical references and index.

1. Introduction -- 2. Classical machine-learning paradigms for data mining -- 3. Supervised learning for misuse/signature detection -- 4. Machine learning for anomaly detection -- 5. Machine learning for hybrid detection -- 6. Machine learning for scan detection -- 7. Machine learning for profiling network traffic -- 8. Privacy-preserving data mining -- 9. Emerging challenges in cybersecurity.

Introducing basic concepts of machine learning and data mining methodologies for cyber security, this book provides a unified reference for specific machine learning solutions and cybersecurity problems. The authors focus on how to apply machine learning methodologies in cybersecurity, categorizing methods for detecting, scanning, profiling, intrusions, and anomalies. The text presents challenges and solutions in machine learning along with cybersecurity fundamentals. It also describes advanced problems in cybersecurity in the machine learning domain and examines privacy-preserving data mining methods as a proactive security solution-- Provided by publisher.

Also available in print edition.

Mode of access: World Wide Web.

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