Anomaly Detection IDS for Detecting DoS Attacks in IoT Networks Based on Machine Learning Algorithms

Widespread and ever-increasing cybersecurity attacks against Internet of Things (IoT) systems are causing a wide range of problems for individuals and organizations. The IoT is self-configuring and open, making it vulnerable to insider and outsider attacks. In the IoT, devices are designed to self-c...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 24; no. 2; p. 713
Main Authors:	Altulaihan, Esra, Almaiah, Mohammed Amin, Aljughaiman, Ahmed
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 01.01.2024 MDPI
Subjects:	Access control Algorithms Automation Classification classifier algorithms Cyberterrorism Data mining Datasets Denial of service attacks Discriminant analysis DoS attacks feature selection IDS Intrusion detection systems IoT network Machine learning Network security Privacy Reputation management Germany DoS attacks IDS machine learning IoT network classifier algorithms feature selection
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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