Can I read Machine Learning Techniques for Cybersecurity on EtoBox?

Machine Learning Techniques for Cybersecurity by Elisa Bertino & Sonam Bhardwaj & Fabrizio Cicala & Sishuai Gong & Imtiaz Karim & Charalampos Katsis & Hyunwoo Lee & Adrian Shuai Li & Ashraf Y. Mahgoub is a nonfiction available to read on EtoBox.

What is Machine Learning Techniques for Cybersecurity about?

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 spe

Who reads Machine Learning Techniques for Cybersecurity?

Author

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

Publisher

Springer International Publishing

Published

2023

Language

EN

ISBN

9783031282591

Category

nonfiction

Subjects

Computer Science, Mathematics, Engineering