£134.87

Springer Deep Learning for Security and Privacy in IoT Book

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Description

Explore the intersection of advanced computing and network safety with Deep Learning for Security and Privacy Preservation in IoT. Published by Springer as part of the Signals and Communication Technology series, this book addresses the growing need for sophisticated protection methods in the Internet of Things landscape. As connected devices become more common, understanding how deep learning can be applied to maintain data integrity and user privacy is essential for researchers and professionals. This technical resource provides a focused look at modern computational approaches to securing complex IoT environments. Whether you are studying computer science or working within the field of artificial intelligence and machine learning, this text offers a structured way to examine how deep learning models can be utilized to defend against modern digital threats. It serves as a specialized addition to your technical library, focusing on the specific challenges found in signal and communication technology.

Key Features

Part of the specialized Signals and Communication Technology series from Springer.

Focuses on the application of deep learning within the Internet of Things (IoT) ecosystem.

Addresses essential topics regarding security and privacy preservation in connected networks.

Designed for readers interested in AI, machine learning, and computer science subjects.

Provides technical insights into protecting data within modern communication technologies.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
04 April 2022
Listed Since
11 August 2021

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