Forthcoming Networks and Sustainability in the AIoT Era Second International Conference FoNeS-AIoT 2024 - Volume 2
by
 
Rasheed, Jawad. editor. (orcid)0000-0003-3761-1641

Title
Forthcoming Networks and Sustainability in the AIoT Era Second International Conference FoNeS-AIoT 2024 - Volume 2

Author
Rasheed, Jawad. editor. (orcid)0000-0003-3761-1641

ISBN
9783031628818

Edition
1st ed. 2024.

Physical Description
VIII, 424 p. 212 illus., 173 illus. in color. online resource.

Series
Lecture Notes in Networks and Systems, 1036

Abstract
This book introduces a groundbreaking approach to enhancing IoT device security, providing a comprehensive overview of its applications and methodologies. Covering a wide array of topics, from crime prediction to cyberbullying detection, from facial recognition to analyzing email spam, it addresses diverse challenges in contemporary society. Aimed at researchers, practitioners, and policymakers, this book equips readers with practical tools to tackle real-world issues using advanced machine learning algorithms. Whether you're a data scientist, law enforcement officer, or urban planner, this book is a valuable resource for implementing predictive models and enhancing public safety measures. It is a comprehensive guide for implementing machine learning solutions across various domains, ensuring optimal performance and reliability. Whether you're delving into IoT security or exploring the potential of AI in urban landscapes, this book provides invaluable insights and tools to navigate the evolving landscape of technology and data science. The book provides a comprehensive overview of the challenges and solutions in contemporary cybersecurity. Through case studies and practical examples, readers gain a deeper understanding of the security concerns surrounding IoT devices and learn how to mitigate risks effectively. The book's interdisciplinary approach caters to a diverse audience, including academics, industry professionals, and government officials, who seek to address the growing cybersecurity threats in IoT environments. Key uses of this book include implementing robust security measures for IoT devices, conducting research on machine learning algorithms for attack detection, and developing policies to enhance cybersecurity in IoT ecosystems. By leveraging advanced machine learning techniques, readers can effectively detect and mitigate cyber threats, ensuring the integrity and reliability of IoT systems. Overall, this book is a valuable resource for anyone involved in designing, implementing, or regulating IoT devices and systems.

Subject Term
Computational intelligence.
 
Artificial intelligence.
 
Engineering -- Data processing.
 
Data Engineering.

Added Author
Rasheed, Jawad.
 
Abu-Mahfouz, Adnan M.
 
Fahim, Muhammad.

Added Corporate Author
SpringerLink (Online service)

Electronic Access
https://doi.org/10.1007/978-3-031-62881-8


LibraryMaterial TypeItem BarcodeShelf Number[[missing key: search.ChildField.HOLDING]]Status
Online LibraryE-Book604064-1001ONLINESpringer E-Kitap Koleksiyonu