Deep Learning Techniques for IoT Security and Privacy

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Beschreibung

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

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Produktinformationen

Titel
Deep Learning Techniques for IoT Security and Privacy
Autor
EAN
9783030890247
ISBN
3030890244
Format
Fester Einband
Herausgeber
Springer International Publishing
Genre
Allgemeines & Lexika
Anzahl Seiten
280
Gewicht
588g
Größe
H241mm x B160mm x T21mm
Jahr
2021
Untertitel
Englisch
Auflage
1st ed. 2022
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