Title:
Data mining and machine learning in cybersecurity
Author:
Dua, Sumeet., author.
ISBN:
9780429063756
9781466508224
Physical Description:
1 online resource (xxii, 234 pages)
General Note:
An Auerbach book.
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.
Abstract:
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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Library | Material Type | Item Barcode | Shelf Number | Status | Item Holds |
|---|---|---|---|---|---|
Searching... | E-Book | 540614-1001 | QA76.9 .D343 D825 2011 | Searching... | Searching... |