Malware Analysis Using Artificial Intelligence and Deep Learning
ISBN-13:
9783030625818
ISBN-10:
3030625818
Edition:
1st ed. 2021
Author:
Mark Stamp, Mamoun Alazab, Andrii Shalaginov
Publication date:
2020
Publisher:
Springer
Format:
Hardcover
671 pages
Category:
AI & Machine Learning
,
Hacking
,
Security & Encryption
,
Engineering
,
Computer Science
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Book details
ISBN-13:
9783030625818
ISBN-10:
3030625818
Edition:
1st ed. 2021
Author:
Mark Stamp, Mamoun Alazab, Andrii Shalaginov
Publication date:
2020
Publisher:
Springer
Format:
Hardcover
671 pages
Category:
AI & Machine Learning
,
Hacking
,
Security & Encryption
,
Engineering
,
Computer Science
Summary
Malware Analysis Using Artificial Intelligence and Deep Learning (ISBN-13: 9783030625818 and ISBN-10: 3030625818), written by authors
Mark Stamp, Mamoun Alazab, Andrii Shalaginov, was published by Springer in 2020.
With an overall rating of 4.5 stars, it's a notable title among other
AI & Machine Learning
(Hacking, Security & Encryption, Engineering, Computer Science) books. You can easily purchase or rent Malware Analysis Using Artificial Intelligence and Deep Learning (Hardcover) from BooksRun,
along with many other new and used
AI & Machine Learning
books
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Description
This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed.
This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.
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