Machine Learning, Deep Learning and AI for Cybersecurity by Mark Stamp

Machine Learning, Deep Learning and AI for Cybersecurity by Mark Stamp

This book addresses a variety of problems that arise at the interface between AI techniques and challenging problems in cybersecurity. The book covers many of the issues that arise when applying AI and deep learning algorithms to inherently difficult problems in the security domain, such as malware detection and analysis, intrusion detection, spam detection, and various other subfields of cybersecurity. The book places particular attention on data driven approaches, where minimal expert domain knowledge is required.

This book bridges some of the gaps that exist between deep learning/AI research and practical problems in cybersecurity. The proposed topics cover a wide range of deep learning and AI techniques, including novel frameworks and development tools enabling the audience to innovate with these cutting-edge research advancements in various security-related use cases. The book is timely since it is not common to find clearly elucidated research that applies the latest developments in AI to problems in cybersecurity.

MARK STAMP, PHD, is Professor of Computer Science at San Jose State University. In addition to his experience working in private industry and academia, Dr. Stamp spent seven years as a cryptanalyst for the U.S. National Security Agency. He is the author of Information Security: Principles and Practice.

RICHARD M. LOW, PHD, is Lecturer in the Department of Mathematics at San Jose State University. His research interests include cryptography, combinatorics, and group theory.