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Handbook of research on machine and deep learning applications for cyber security

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Handbook of research on machine and deep learning applications for cyber security/ Padmavathi Ganapathi and D. Shanmugapriya, editors.
other author:	Ganapathi, Padmavathi,
Published:	Hershey, Pennsylvania :IGI Global, : 2020.,
Description:	1 online resource (482 p.)
Subject:	Computer networks - Security measures. -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-9611-0
ISBN:	9781522596134 (ebk.)

Handbook of research on machine and deep learning applications for cyber security
Handbook of research on machine and deep learning applications for cyber security[electronic resource] /Padmavathi Ganapathi and D. Shanmugapriya, editors. - Hershey, Pennsylvania :IGI Global,2020. - 1 online resource (482 p.)

Includes bibliographical references and index.

Chapter 1. Review on intelligent algorithms for cyber security -- Chapter 2. A review on cyber security mechanisms using machine and deep learning algorithms -- Chapter 3. Review on machine and deep learning applications for cyber security -- Chapter 4. Applications of machine learning in cyber security domain -- Chapter 5. Applications of machine learning in cyber security -- Chapter 6. Malware and anomaly detection using machine learning and deep learning methods -- Chapter 7. Cyber threats detection and mitigation using machine learning -- Chapter 8. Hybridization of machine learning algorithm in intrusion detection system -- Chapter 9. A hybrid approach to detect the malicious applications in android-based smartphones using deep learning -- Chapter 10. Anomaly-based intrusion detection: adapting to present and forthcoming communication environments -- Chapter 11. Traffic analysis of UAV networks using enhanced deep feed forward neural networks (EDFFNN) -- Chapter 12. A novel biometric image enhancement approach with the hybridization of undecimated wavelet transform and deep autoencoder -- Chapter 13. A 3D-cellular automata-based publicly-verifiable threshold secret sharing -- Chapter 14. Big data analytics for intrusion detection: an overview -- Chapter 15. Big data analytics with machine learning and deep learning methods for detection of anomalies in network traffic -- Chapter 16. A secure protocol for high-dimensional big data providing data privacy -- Chapter 17. A review of machine learning methods applied for handling zero-day attacks in the cloud environment -- Chapter 18. Adoption of machine learning with adaptive approach for securing CPS -- Chapter 19. Variable selection method for regression models using computational intelligence techniques.

"This book explores the use of machine learning and deep learning applications in the areas of cyber security and cyber-attack handling mechanisms"--

ISBN: 9781522596134 (ebk.)Subjects--Topical Terms:

555385
Computer networks
--Security measures.

LC Class. No.: TK5105.59 / .H35325 2020e

Dewey Class. No.: 006.3/1

Handbook of research on machine and deep learning applications for cyber security
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245 0 0 $a Handbook of research on machine and deep learning applications for cyber security $h [electronic resource] / $c Padmavathi Ganapathi and D. Shanmugapriya, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2020.
300 $a 1 online resource (482 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Review on intelligent algorithms for cyber security -- Chapter 2. A review on cyber security mechanisms using machine and deep learning algorithms -- Chapter 3. Review on machine and deep learning applications for cyber security -- Chapter 4. Applications of machine learning in cyber security domain -- Chapter 5. Applications of machine learning in cyber security -- Chapter 6. Malware and anomaly detection using machine learning and deep learning methods -- Chapter 7. Cyber threats detection and mitigation using machine learning -- Chapter 8. Hybridization of machine learning algorithm in intrusion detection system -- Chapter 9. A hybrid approach to detect the malicious applications in android-based smartphones using deep learning -- Chapter 10. Anomaly-based intrusion detection: adapting to present and forthcoming communication environments -- Chapter 11. Traffic analysis of UAV networks using enhanced deep feed forward neural networks (EDFFNN) -- Chapter 12. A novel biometric image enhancement approach with the hybridization of undecimated wavelet transform and deep autoencoder -- Chapter 13. A 3D-cellular automata-based publicly-verifiable threshold secret sharing -- Chapter 14. Big data analytics for intrusion detection: an overview -- Chapter 15. Big data analytics with machine learning and deep learning methods for detection of anomalies in network traffic -- Chapter 16. A secure protocol for high-dimensional big data providing data privacy -- Chapter 17. A review of machine learning methods applied for handling zero-day attacks in the cloud environment -- Chapter 18. Adoption of machine learning with adaptive approach for securing CPS -- Chapter 19. Variable selection method for regression models using computational intelligence techniques.
520 3 $a "This book explores the use of machine learning and deep learning applications in the areas of cyber security and cyber-attack handling mechanisms"-- $c Provided by publisher.
650 0 $a Computer networks $x Security measures. $3 555385
650 0 $a Computer security $x Data processing. $3 1235103
650 0 $a Computer crimes $x Prevention $x Data processing. $3 1340814
650 0 $a Machine learning. $3 561253
700 1 $a Ganapathi, Padmavathi, $d 1964- $3 1340812
700 1 $a Shanmugapriya, D., $d 1978- $3 1340813
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-9611-0