Malware Analysis Using Artificial Intelligence and Deep Learning

by Mark Stamp (Editor), Mamoun Alazab (Editor), Andrii Shalaginov (Editor)

​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.

671 pages, Hardcover

Published December 21, 2020

About the author

Mark Stamp, Ph.D., is a professor of computer science at San Jose State University (San Jose, California).