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Machine learning approaches in cyber...

Emmanuel, Sabu.

Machine learning approaches in cyber security analytics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning approaches in cyber security analyticsby Tony Thomas, Athira P. Vijayaraghavan, Sabu Emmanuel.
Author:	Thomas, Tony.
other author:	P. Vijayaraghavan, Athira.
Published:	Singapore :Springer Singapore :2020.
Description:	xi, 209 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Computer security.
Online resource:	https://doi.org/10.1007/978-981-15-1706-8
ISBN:	9789811517068$q(electronic bk.)

Machine learning approaches in cyber security analytics
Thomas, Tony.

Machine learning approaches in cyber security analytics[electronic resource] /by Tony Thomas, Athira P. Vijayaraghavan, Sabu Emmanuel. - Singapore :Springer Singapore :2020. - xi, 209 p. :ill., digital ;24 cm.

Chapter 1. Introduction -- Chapter 2. Machine Learning Algorithms -- Chapter 3. Machine Learning in Cyber Security Analytics -- Chapter 4. Applications of Support Vector Machines -- Chapter 5. Applications of Nearest Neighbor -- Chapter 6. Applications of Clustering -- Chapter 7. Applications of Dimensionality Reduction -- Chapter 8. Applications of other Machine Learning Methods.

This book introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.

ISBN: 9789811517068$q(electronic bk.)

Standard No.: 10.1007/978-981-15-1706-8doiSubjects--Topical Terms:

184416
Computer security.

LC Class. No.: QA76.9.A25 / T46 2020

Dewey Class. No.: 005.8

Machine learning approaches in cyber security analytics
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245 1 0 $a Machine learning approaches in cyber security analytics $h [electronic resource] / $c by Tony Thomas, Athira P. Vijayaraghavan, Sabu Emmanuel.
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300 $a xi, 209 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1. Introduction -- Chapter 2. Machine Learning Algorithms -- Chapter 3. Machine Learning in Cyber Security Analytics -- Chapter 4. Applications of Support Vector Machines -- Chapter 5. Applications of Nearest Neighbor -- Chapter 6. Applications of Clustering -- Chapter 7. Applications of Dimensionality Reduction -- Chapter 8. Applications of other Machine Learning Methods.
520 $a This book introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.
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650 2 4 $a Data Structures. $3 273992
700 1 $a P. Vijayaraghavan, Athira. $3 863611
700 1 $a Emmanuel, Sabu. $3 863612
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