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Advanced Machine Learning for Cyber-Attack Detection in Iot Networks - by Dinh Thai Hoang & Nguyen Quang Hieu & Diep N Nguyen & Ekram Hossain

Advanced Machine Learning for Cyber-Attack Detection in Iot Networks - by  Dinh Thai Hoang & Nguyen Quang Hieu & Diep N Nguyen & Ekram Hossain - 1 of 1
$190.00 when purchased online
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About this item

Highlights

  • Advanced Machine Learning for Cyber-Attack Detection in IoT Networks analyzes diverse machine learning techniques, including supervised, unsupervised, reinforcement, and deep learning, along with their applications in detecting and preventing cyberattacks in future IoT systems.
  • Author(s): Dinh Thai Hoang & Nguyen Quang Hieu & Diep N Nguyen & Ekram Hossain
  • 424 Pages
  • Computers + Internet, Intelligence (AI) & Semantics

Description



Book Synopsis



Advanced Machine Learning for Cyber-Attack Detection in IoT Networks analyzes diverse machine learning techniques, including supervised, unsupervised, reinforcement, and deep learning, along with their applications in detecting and preventing cyberattacks in future IoT systems. Chapters investigate the key challenges and vulnerabilities found in IoT security, how to handle challenges in data collection and pre-processing specific to IoT environments, as well as what metrics to consider for evaluating the performance of machine learning models. Other sections look at the training, validation, and evaluation of supervised learning models and present case studies and examples that demonstrate the application of supervised learning in IoT security.
Dimensions (Overall): 9.29 Inches (H) x 7.48 Inches (W) x .79 Inches (D)
Weight: 1.8 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 424
Genre: Computers + Internet
Sub-Genre: Intelligence (AI) & Semantics
Publisher: Academic Press
Format: Paperback
Author: Dinh Thai Hoang & Nguyen Quang Hieu & Diep N Nguyen & Ekram Hossain
Language: English
Street Date: May 28, 2025
TCIN: 1006342664
UPC: 9780443290329
Item Number (DPCI): 247-50-5022
Origin: Made in the USA or Imported

Shipping details

Estimated ship dimensions: 0.79 inches length x 7.48 inches width x 9.29 inches height
Estimated ship weight: 1.8 pounds
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