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Protecting IoT devices from security attacks using effective decision-making strategy of appropriate features

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Abstract

The term "Internet of things (IoT)” refers to a network in which data from all connected devices may be gathered, analyzed, and modified as per requirements to offer new services. IoT devices require a constant Internet connection to exchange data. The volume and speed of data continue to grow quickly with the expansion of IoT devices nowadays. IoT systems frequently use messaging protocols to exchange IoT data. IoT security must be established using advanced techniques as it is vulnerable to many threats. The primary objectives of IoT security are to protect customer privacy, data integrity, and confidentiality, as well as the security of assets and IoT devices and the accessibility of services provided by an IoT ecosystem. In this regard, the IoT must meet user demands while consuming the least number of resources, including money, vitality, and time. The proposed research work is organized into numerous categories to make it easier for researchers and readers to solve and understand security problems in IOT devices. The categories “Features” are identified from available literature, and a specific criterion is adopted for choosing alternatives. The entropy approach to determine criterion relevance by calculating features weights is utilized. The second method “EDAS” approach is used and the alternatives are sorted chronologically based on the criterion weights for easy identification and selection of an effective alternative. Finally, all alternatives are precisely analyzed and ranked. Using our research method, various appropriate features are extracted and are evaluated to solve security issue within IoT devices. The most significant features are ranked to help researchers and manufacturers to focus on security-related issues in IoT devices.

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Data availability

The dataset used for this study is available on reasonable request from the corresponding author.

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Funding

This research received no external funding.

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Gachon University, Seongnam, 13120, Republic of Korea

    Inam Ullah

  2. Department of Computer Science, University of Swabi, Swabi, Pakistan

    Asra Noor, Shah Nazir & Farhad Ali

  3. Department of Computer Science, Al Ain University, P.O. Box 112612, Abu Dhabi, United Arab Emirates

    Yazeed Yasin Ghadi

  4. SAUDI ARAMCO Cybersecurity Chair, Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, 31441, Dammam, Saudi Arabia

    Nida Aslam

Authors
  1. Inam Ullah
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  2. Asra Noor
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  3. Shah Nazir
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  4. Farhad Ali
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  5. Yazeed Yasin Ghadi
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  6. Nida Aslam
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Contributions

I.U. was involved in conceptualization, data curation, methodology, and hardware. I.U., A.N., and F.A. were involved in formal analysis. I.U. and A.N. contributed to software; S.N. was involved in supervision; F.A. and Y.Y.G. were involved in visualization; I.U. and F.A. were involved in writing—original draft; and A.N., F.A., S.N., Y.Y.G., and N.A. were involved in writing—review and editing. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Asra Noor.

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Ullah, I., Noor, A., Nazir, S. et al. Protecting IoT devices from security attacks using effective decision-making strategy of appropriate features. J Supercomput 80, 5870–5899 (2024). https://doi.org/10.1007/s11227-023-05685-3

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  • DOI: https://doi.org/10.1007/s11227-023-05685-3

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