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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.
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.
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Silicon Valley Cybersecurity Conference - Second Conference, SVCC 2021, San Jose, CA, USA, December 2-3, 2021, Revised Selected Papers (Paperback, 1st ed. 2022)
Sang-Yoon Chang, Luis Bathen, Fabio Di Troia, Thomas H. Austin, Alex J. Nelson
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R712
Discovery Miles 7 120
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Ships in 10 - 15 working days
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This book constitutes selected and revised papers from the Second
Silicon Valley Cybersecurity Conference, held in San Jose, USA, in
December 2021. Due to the COVID-19 pandemic the conference was held
in a virtual format. The 9 full papers and one shoprt paper
presented in this volume were thoroughly reviewed and selected from
15 submissions. They present most recent research on dependability,
reliability, and security to address cyber-attacks,
vulnerabilities, faults, and errors in networks and systems.
Chapters 1, 4, 5, 6, and 8-10 are published open access under a CC
BY license (Creative Commons Attribution 4.0 International
License).
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