Machine Learning for Computer and Cyber Security

Name: Machine Learning for Computer and Cyber Security
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SKU: 9781138587304
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Principle, Algorithms, and Practices

Series: Cyber Ecosystem and Security

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Summary

Machine Learning for Computer and Cyber Security explores the intersection of machine learning techniques with the vital fields of computer and cyber security. The book addresses how machine learning and data mining can detect anomalies to protect computing systems and networks from threats such as unauthorised access and phishing scams. It covers current security challenges, demonstrates practical algorithms with examples, and offers insights into future research directions. This resource is tailored for IT professionals, researchers, and students seeking to enhance cyber defence strategies through advanced computing methodologies.
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Format: Hardback

$412⁰⁰

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Machine Learning for Computer and Cyber Security

$412⁰⁰

Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?

This book is ideal for IT professionals, cybersecurity experts, researchers, graduate students, and software developers specialising in computer science and engineering fields interested in machine learning applications for security purposes. It serves as both an educational and reference tool for those aiming to deepen their knowledge and develop innovative solutions against cyber threats.

This comprehensive book offers valuable insights while using a wealth of examples and illustrations to effectively demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security.

Description

While Computer Security is a broader term that incorporates technologies, protocols, standards, and policies to ensure the security of computing systems—including computer hardware, software, and the information stored within it—Cyber Security is a specific, growing field focused on protecting computer networks (both offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning, a branch of Computer Science, enables computing machines to adopt new behaviours based on observable and verifiable data and information. It can be applied to ensure the security of computers and information by detecting anomalies using data mining and other techniques.

Machine Learning for Computer and Cyber Security is an invaluable resource for understanding the importance of machine learning and data mining in establishing computer and cyber security. It emphasises important security aspects associated with computer and cyber security, along with the analysis of machine learning and data mining-based solutions. The book also highlights future research domains where these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars, and software developers seeking to conduct research and develop combating solutions in cyber security using machine learning approaches. It is an extensive source of information for readers in the field of Computer Science and Engineering, as well as Cyber Security professionals.

Key Features:

This book contains examples and illustrations to demonstrate the principles, algorithms, challenges, and applications of machine learning and data mining for computer and cyber security.
It showcases important security aspects and current trends in the field.
It provides insight into future research directions in the field.
The content helps students prepare to exercise better defence by understanding attackers' motivations and how to deal with and mitigate situations using machine learning-based approaches.

Series: Cyber Ecosystem and Security

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Machine Learning for Computer and Cyber Security

Hardback

$412⁰⁰

Available
Ships in 4-6 weeks

Book Details

INFORMATION

ISBN: 9781138587304

Publisher: Taylor & Francis Ltd

Format: Hardback

Date Published: 13 February 2019

Country: United Kingdom

Imprint: CRC Press

Illustration: 49 Tables, black and white; 8 Illustrations, color; 126 Illustrations, black and white

Contributors:

Edited by Brij B. Gupta
Edited by Quan Z. Sheng

Audience: Professional and scholarly

DIMENSIONS

Width: 156.0mm

Height: 234.0mm

Weight: 740g

Pages: 352

Collections

Computing & Technology Education & Reference Non-Fiction Series: Cyber Ecosystem and Security

About the Author

Brij B. Gupta received PhD degree from Indian Institute of Technology Roorkee, India in Information and Cyber Security. He published more than 175 research papers in International Journals and Conferences of high repute including IEEE, Elsevier, ACM, Springer, Wiley, Taylor & Francis, Inderscience, etc. He has visited several countries, i.e. Canada, Japan, Malaysia, Australia, China, Hong-Kong, Italy, Spain etc to present his research work. His biography was selected and published in the 30th Edition of Marquis Who's Who in the World, 2012. Dr. Gupta also received Young Faculty research fellowship award from Ministry of Electronics and Information Technology, Government of India in 2017. He is also working as principal investigator of various R&D projects. He is serving as associate editor of IEEE Access, IEEE TII, and Executive editor of IJITCA, Inderscience, respectively. At present, Dr. Gupta is working as Assistant Professor in the Department of Computer Engineering, National Institute of Technology Kurukshetra India. His research interest includes Information security, Cyber Security, Mobile security, Cloud Computing, Web security, Intrusion detection and Phishing.

Michael Sheng is a full Professor and Head of Department of Computing at Macquarie University. Before moving to Macquarie, Michael spent 10 years at School of Computer Science, the University of Adelaide (UoA). Michael holds a PhD degree in computer science from the University of New South Wales (UNSW) and did his post-doc as a research scientist at CSIRO ICT Centre. From 1999 to 2001, Sheng also worked at UNSW as a visiting research fellow. Prior to that, he spent 6 years as a senior software engineer in industries.

Prof. Sheng has more than 280 publications as edited books and proceedings, refereed book chapters, and refereed technical papers in journals and conferences including ACM Computing Surveys, ACM TOIT, ACM TOMM, ACM TKDD, VLDB Journal, Computer (Oxford), IEEE TPDS, TKDE, DAPD, IEEE TSC, WWWJ, IEEE Computer, IEEE Internet Computing, Communications of the ACM, VLDB, ICDE, ICDM, CIKM, EDBT, WWW, ICSE, ICSOC, ICWS, and CAiSE. Dr. Michael Sheng is the recipient of the ARC Future Fellowship (2014), Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003). He is a member of the IEEE and the ACM. Homepage: https://web.science.mq.edu.au/~qsheng/

Machine Learning for Computer and Cyber Security