Malware Analysis Using Artificial Intelligence and Deep Learning

Name: Malware Analysis Using Artificial Intelligence and Deep Learning
SKU: 978-3-030-62584-9
Price: 215.00 CHF
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Artikelnummer: 978-3-030-62584-9

Einband: Kartonierter Einband (Kt)

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¿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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Verlag	Springer
Einband	Kartonierter Einband (Kt)
Erscheinungsjahr	2021
Seitenangabe	672 S.
Ausgabekennzeichen	Englisch
Masse	H23.5 cm x B15.5 cm x D3.6 cm 1'001 g
Autor	Stamp, Mark (Hrsg.) / Alazab, Mamoun (Hrsg.) / Shalaginov, Andrii (Hrsg.)

Über den Autor Mark (Hrsg.) Stamp

Mark Stamp has been active in the field of information security for more than three decades. Following his Ph.D. research in cryptography, he spent the better part of a decade as a cryptanalyst with the US National Security Agency (NSA), followed by two years developing a cybersecurity product for a Silicon Valley startup company. For the past 20 years, Dr. Stamp has been a faculty member in the Department of Computer Science at San Jose State University, where he has developed and regularly teaches courses in information security and machine learning. He has published more than 175 research articles, most of which are at the interface between information security and machine learning. Dr. Stamp has served as a co-editor for several books, including the Handbook of Information and Communication Security (Springer, 2010) and Malware Analysis Using Artificial Intelligence and Deep Learning (Springer, 2021). Martin Jurecek is an assistant professor in computer science at Czech Technical University in Prague. He graduated from the Charles University in Prague, Faculty of Mathematics and Physics, with a specialization in mathematical methods of information security. He received his Ph.D. at the Czech Technical University in Prague, Faculty of Information Technology, specializing in automatic malware detection. Dr. Jurecek worked for five years as a malware researcher in the antivirus industry and two years as a data scientist on several projects in the field of information security for the banking and telecommunications sectors. He has been working as an assistant professor at the Czech Technical University in Prague for over ten years. His main research interests focus on the application of machine learning and artificial intelligence approaches to malware detection. Other areas of his interest are algebraic cryptanalysis and the security of cryptocurrencies.