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Machine Learning Techniques for Cybersecurity (Synthesis Lectures on Information Security, Privacy, and Trust) book cover by Elisa Bertino, Sonam Bhardwaj, Fabrizio Cicala, Sishuai Gong, Imtiaz Karim, Charalampos Katsis, Hyunwoo Lee, Adrian Shuai Li, Ashraf Y. Mahgoub
Hardcover

Machine Learning Techniques for Cybersecurity (Synthesis Lectures on Information Security, Privacy, and Trust)

by Elisa Bertino, Sonam Bhardwaj, Fabrizio Cicala, Sishuai Gong, Imtiaz Karim, Charalampos Katsis, Hyunwoo Lee, Adrian Shuai Li and Ashraf Y. Mahgoub

$43.99 / copy at 25+ copies As low as $42.99 at 100+Your best volume price

Total $1,099.75

Hardcover · 165 pages Springer International Publishing · 2023

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About the book

Machine Learning Techniques for Cybersecurity (Synthesis Lectures on Information Security, Privacy, and Trust)

This book explores machine learning (ML) defenses against the many cyberattacks that make our workplaces, schools, private residences, and critical infrastructures vulnerable as a consequence of the dramatic increase in botnets, data ransom, system and network denials of service, sabotage, and data theft attacks. The use of ML techniques for security tasks has been steadily increasing in research and also in practice over the last 10 years. Covering efforts to devise more effective defenses, the book explores security solutions that leverage machine learning (ML) techniques that have recently grown in feasibility thanks to significant advances in ML combined with big data collection and analysis capabilities. Since the use of ML entails understanding which techniques can be best used for specific tasks to ensure comprehensive security, the book provides an overview of the current state of the art of ML techniques for security and a detailed taxonomy of security tasks and corresponding ML techniques that can be used for each task. It also covers challenges for the use of ML for security tasks and outlines research directions. 

While many recent papers have proposed approaches for specific tasks, such as software security analysis and anomaly detection, these approaches differ in many aspects, such as with respect to the types of features in the model and the dataset used for training the models. In a way that no other available work does, this book provides readers with a comprehensive view of the complex area of ML for security, explains its challenges, and highlights areas for future research. This book is relevant to graduate students in computer science and engineering as well as information systems studies, and will also be useful to researchers and practitioners who work in the area of ML techniques for security tasks.



The book, Machine Learning Techniques for Cybersecurity (Synthesis Lectures on Information Security, Privacy, and Trust) [Bulk, Wholesale, Quantity] ISBN#9783031282584 in Hardcover by Elisa Bertino, Sonam Bhardwaj, Fabrizio Cicala, Sishuai Gong, Imtiaz Karim, Charalampos Katsis, Hyunwoo Lee, Adrian Shuai Li, Ashraf Y. Mahgoub may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.

Details

Publisher
Springer International Publishing
Authors
Elisa Bertino, Sonam Bhardwaj, Fabrizio Cicala, Sishuai Gong, Imtiaz Karim, Charalampos Katsis, Hyunwoo Lee, Adrian Shuai Li, Ashraf Y. Mahgoub
Format
Hardcover
Published
Apr 9, 2023
ISBN-13
9783031282584
Pages
165
Printing
Printed on demand
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