Handbook of research on machine and deep learning applications for cyber security/ Padmavathi Ganapathi and D. Shanmugapriya, editors.

Shanmugapriya D.,; Ganapathi Padmavathi

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dc.contributor.author	Ganapathi Padmavathi
dc.contributor.author	Shanmugapriya D.,
dc.date.accessioned	2024-01-29T22:13:22Z
dc.date.available	2024-01-29T22:13:22Z
dc.date.issued	2020
dc.identifier.citation	Handbook of research on machine and deep learning applications for cyber security - 1 online resource (482 pages) - URL: https://libweb.kpfu.ru/ebsco/pdf/2227914.pdf
dc.identifier.isbn	1522596135
dc.identifier.isbn	9781522596141
dc.identifier.isbn	1522596143
dc.identifier.isbn	9781522596134
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/180415
dc.description	Includes bibliographical references and index.
dc.description.abstract	"This book explores the use of machine learning and deep learning applications in the areas of cyber security and cyber-attack handling mechanisms"--
dc.description.tableofcontents	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.
dc.language	English
dc.language.iso	en
dc.subject.other	Computer networks -- Security measures.
dc.subject.other	Computer security -- Data processing.
dc.subject.other	Computer crimes -- Prevention -- Data processing.
dc.subject.other	Machine learning.
dc.subject.other	Electronic books.
dc.title	Handbook of research on machine and deep learning applications for cyber security/ Padmavathi Ganapathi and D. Shanmugapriya, editors.
dc.type	Book
dc.contributor.org	IGI Global,
dc.description.pages	1 online resource (482 pages)
dc.collection	Электронно-библиотечные системы
dc.source.id	EN05CEBSCO05C1456