Malware Analysis Using Artificial Intelligence and Deep Learning (Hardcover, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	December 2020
First published:	2021
Editors:	Mark Stamp • Mamoun Alazab • Andrii Shalaginov
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	651
Edition:	1st ed. 2021
ISBN-13:	978-3-03-062581-8
Categories:	Books > Computing & IT > Computer communications & networking > Network security Books > Computing & IT > Social & legal aspects of computing > Computer fraud & hacking Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	3-03-062581-8
Barcode:	9783030625818

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