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RETRACTED ARTICLE: Intrusion detection based on machine learning in the internet of things, attacks and counter measures

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This article was retracted on 13 February 2024

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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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Acknowledgments

This work was supported by Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (P0008703, The Competency Development Program for Industry Specialist) and also the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2021-2018-0-01799) supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation).

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  1. Department of Software Engineering, Foundation University Islamabad, Islamabad, 44000, Pakistan

    Eid Rehman, Muhammad Haseeb-ud-Din, Arif Jamal Malik, Tehmina Karmat Khan & Aaqif Afzaal Abbasi

  2. Faculty of Applied Computing and Technology, Noroff University College, Kristiansand, Norway

    Seifedine Kadry

  3. Department of Computer Science, HITEC University Taxila, Taxila, Pakistan

    Muhammad Attique Khan

  4. Chung-Ang University - Seoul Campus: Chung-Ang University, Seoul, Korea

    Seungmin Rho

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Rehman, E., Haseeb-ud-Din, M., Malik, A.J. et al. RETRACTED ARTICLE: Intrusion detection based on machine learning in the internet of things, attacks and counter measures. J Supercomput 78, 8890–8924 (2022). https://doi.org/10.1007/s11227-021-04188-3

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