Feature Selection and Feature Extraction in Machine Learning-Based IoT Intrusion Detection System

Language: English

Published by Eliva Press, 2024

9999317790 / 9789999317795

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Softcover

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nach der Bestellung gedruckt Neuware - Printed after ordering - 'In a world increasingly reliant on Internet of Things (IoT) devices, ensuring their security is paramount. Yet, these very devices are vulnerable to cyberattacks, posing significant threats to individuals and organizations alike. To combat this, machine learning has emerged as a powerful tool for network intrusion detection in IoT environments.Delving deep into this intersection of cybersecurity and machine learning, this book presents a comprehensive exploration of feature reduction techniques for IoT network intrusion detection. Drawing from extensive research, it offers a meticulous comparison of feature extraction and selection methods within a machine learning-based attack classification framework.Through rigorous analysis of performance metrics such as accuracy, f1-score, and runtime, the book sheds light on the efficacy of these techniques on the heterogeneous IoT dataset known as Network TON-IoT. Unveiling key insights, it reveals that while feature extraction tends to outperform feature selection in detection performance, the latter exhibits advantages in model training and inference time.But the findings don't stop there. The book delves deeper into the nuances of IoT security, addressing the challenges posed by computational resource constraints. It underscores the importance of feature reduction in constructing lightweight yet effective intrusion detection models tailored for IoT scenarios.Moreover, the book offers practical guidance for selecting intrusion detection methods tailored to specific IoT environments. By analyzing the trade-offs between feature extraction and selection, it equips readers with the knowledge to navigate the complexities of IoT security.'.…

Seller Inventory # 9789999317795

Title
Feature Selection and Feature Extraction in Machine Learning-Based IoT Intrusion Detection System
Author
Jing Li
Publisher
Eliva Press
Publication year
2024
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
9999317790
ISBN 13
9789999317795
Item weight
95 grams
Dimensions
229x152x3 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

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