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Cybersecurity for artificial intelligence / Mark Stamp, Corrado Aaron Visaggio, Francesco Mercaldo, Fabio Di Troia, editors.

Stamp, Mark, editor.; Aaron Visaggio, Corrado, editor.; Mercaldo, Francesco, editor.; Di Troia, Fabio, editor.
2022
Q335
Available Online
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Title
Cybersecurity for artificial intelligence / Mark Stamp, Corrado Aaron Visaggio, Francesco Mercaldo, Fabio Di Troia, editors.
ISBN
9783030970871 (electronic bk.)
3030970876 (electronic bk.)
9783030970864
DOI
https://doi.org/10.1007/978-3-030-97087-1
Published
Cham, Switzerland : Springer, 2022.
Language
English
Description
1 online resource (xvi, 380 pages) : illustrations (some color).
Item Number
10.1007/978-3-030-97087-1 doi
Call Number
Q335
Dewey Decimal Classification
006.3
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed July 19, 2022).
Added Author
Stamp, Mark, editor.
Aaron Visaggio, Corrado, editor.
Mercaldo, Francesco, editor.
Di Troia, Fabio, editor.
Series
Advances in information security ; 54.
Linked Resources
Online Access
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Part I: Malware-Related Topics
Generation of Adversarial Malware and Benign Examples using Reinforcement Learning
Auxiliary-Classifier GAN for Malware Analysis
Assessing the Robustness of an Image-based Malware Classifier with Small Level Perturbations Techniques
Detecting Botnets Through Deep Learning and Network Flow Analysis
Interpretability of Machine Learning-Based Results of Malware Detection Using a Set of Rules
Mobile Malware Detection using Consortium Blockchain
BERT for Malware Classification
Machine Learning for Malware Evolution Detection
Part II: Other Security Topics
Gambling for Success: The Lottery Ticket Hypothesis in Deep Learning-based Side-channel Analysis
Evaluating Deep Learning Models and Adversarial Attacks on Accelerometer-Based Gesture Authentication
Clickbait Detection for YouTube Videos
Survivability Using Artificial Intelligence Assisted Cyber Risk Warning
Machine Learning and Deep Learning for Fixed-Text Keystroke Dynamics
Machine Learning-Based Analysis of Free-Text Keystroke Dynamic
Free-Text Keystroke Dynamics for User Authentication.

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