This book contains contemporary research that outlines and addresses
security, privacy challenges and decision-making in IoT environments.
The authors provide a variety of subjects related to the following
Keywords: IoT, security, AI, deep learning, federated learning,
intrusion detection systems, and distributed computing paradigms. This
book also offers a collection of the most up-to-date research,
providing a complete overview of security and privacy-preserving in
IoT environments. It introduces new approaches based on machine
learning that tackles security challenges and provides the field
with new research material that’s not covered in the primary
literature. The Internet of Things (IoT) refers to a network of tiny
devices linked to the Internet or other communication networks. IoT is
gaining popularity, because it opens up new possibilities for
developing many modern applications. This would include smart cities,
smart agriculture, innovative healthcare services and more. The
worldwide IoT market surpassed $100 billion in sales for the first
time in 2017, and forecasts show that this number might reach $1.6
trillion by 2025. However, as IoT devices grow more widespread,
threats, privacy and security concerns are growing. The massive volume
of data exchanged highlights significant challenges to preserving
individual privacy and securing shared data. Therefore, securing the
IoT environment becomes difficult for research and industry
stakeholders. Researchers, graduate students and educators in the
fields of computer science, cybersecurity, distributed systems and
artificial intelligence will want to purchase this book. It will also
be a valuable companion for users and developers interested in
decision-making and security risk management in IoT environments.
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Produktdetaljer
ISBN
9783031475900
Publisert
2024
Utgiver
Vendor
Springer
Språk
Product language
Engelsk
Format
Product format
Digital bok