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The Journal of Supercomputing
Erschienen in: The Journal of Supercomputing 6/2022

14.01.2022

RETRACTED ARTICLE: Intrusion detection based on machine learning in the internet of things, attacks and counter measures

verfasst von: Eid Rehman, Muhammad Haseeb-ud-Din, Arif Jamal Malik, Tehmina Karmat Khan, Aaqif Afzaal Abbasi, Seifedine Kadry, Muhammad Attique Khan, Seungmin Rho

Erschienen in: The Journal of Supercomputing | Ausgabe 6/2022

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Abstract

Globally, data security and privacy over the Internet of Things (IoT) are necessary due to its emergence in daily life. As the IoT will soon invade each part of our lives, attention to IoT security is significant. The nature of attacks is dynamic, and addressing this requires designing dynamic methods and a self-adaptable scheme to discover security attacks from malicious use of IoT equipment. The best detection mechanism against attacks from compromised IoT devices includes machine learning techniques. This study emphasizes the latest literature on attack types and uses a scheme based on machine learning for network support in IoT and intrusion detection. Therefore, the current work includes a thorough analysis of multiple intelligence methods and their deployed architectures of network intrusion detection, focusing on IoT attacks and machine learning-based intrusion detection schemes. Moreover, it explores methods based on machine learning appropriate for identifying IoT devices associated with cyber attacks.
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Metadaten
Titel
RETRACTED ARTICLE: Intrusion detection based on machine learning in the internet of things, attacks and counter measures
verfasst von
Eid Rehman
Muhammad Haseeb-ud-Din
Arif Jamal Malik
Tehmina Karmat Khan
Aaqif Afzaal Abbasi
Seifedine Kadry
Muhammad Attique Khan
Seungmin Rho
Publikationsdatum
14.01.2022
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 6/2022
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-021-04188-3

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