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Artificial Intelligence for Cybersecurity (1st ed. 2022) Loot Price: R4,266
Discovery Miles 42 660
Artificial Intelligence for Cybersecurity (1st ed. 2022): Mark Stamp, Corrado Aaron Visaggio, Francesco Mercaldo, Fabio Di Troia

Artificial Intelligence for Cybersecurity (1st ed. 2022)

Mark Stamp, Corrado Aaron Visaggio, Francesco Mercaldo, Fabio Di Troia

Series: Advances in Information Security, 54

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Loot Price R4,266 Discovery Miles 42 660 | Repayment Terms: R400 pm x 12*

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This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: Advances in Information Security, 54
Release date: July 2023
First published: 2022
Editors: Mark Stamp • Corrado Aaron Visaggio • Francesco Mercaldo • Fabio Di Troia
Dimensions: 235 x 155mm (L x W)
Pages: 380
Edition: 1st ed. 2022
ISBN-13: 978-3-03-097089-5
Categories: Books
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LSN: 3-03-097089-2
Barcode: 9783030970895

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