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Deep Learning Techniques for IoT Security and Privacy de Mohamed Abdel-Basset

Deep Learning Techniques for IoT Security and Privacy: Studies in Computational Intelligence, cartea 997

Autor Mohamed Abdel-Basset, Nour Moustafa, Hossam Hawash, Weiping Ding
en Limba Engleză Paperback – 7 dec 2022
This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.
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Specificații

ISBN-13: 9783030890278
ISBN-10: 3030890279
Pagini: 257
Ilustrații: XXI, 257 p. 71 illus., 69 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.4 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Chapter 1, Conceptualization of Security, Forensics, and Privacy of Internet of Things.- Chapter 2, Internet of Things, Preliminaries and Foundations.- Chapter 3, Internet of Things Security Requirements, Threats, Countermeasures.- Chapter 4, Digital Forensics in Internet of Things.- Chapter 5, Supervised Deep Learning for Secure Internet of Things.- Chapter 6, Unsupervised Deep Learning for Secure Internet of Things.- Chapter 7, Semi-supervised Deep Learning for Secure Internet of Things.- Chapter 8, Reinforcement Learning for Secure Internet of Things.- Chapter 9, Federated Learning for Privacy-Preserving Internet of Things.- Chapter 10, Challenges, Opportunities, and Future Prospects.

Textul de pe ultima copertă

This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.

Caracteristici

Presents a Machine Learning Approach to Conducting Digital Forensics Contains state-of-the-art research and shows how to teach hands-on incident response and digital forensic courses Covers the applications of digital forensics and artificial intelligence in operating systems