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AI-assisted bio-inspired algorithm for secure IoT communication networks

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Abstract

The Internet of Things (IoT) is made up of intelligent devices that interact with each other. It allows information to be gathered and shared by these devices. In addition, IoT now has a wide range of life applications such as business, logistics, health monitoring, smart ecosystem, and information concerning individuals, social and private environments. Security-related issues involved in such a communication network are drastically increasing day by day. Therefore, existing authentication and authorization concepts must grow along with technological evolution. This paper presents an artificial intelligence (AI)-assisted Bio-inspired algorithm for secure IoT communication networks (AI-BIAS) to improve future communication. The proposed framework is categorized into two sections: First, the Bio-inspired algorithm-assisted blockchain technology for authentication and authorization in the IoT communication network is presented. Further, the Artificial Intelligence algorithm monitors the proposed IoT communication network. The experimental results show that the proposed model enhances the accuracy ratio of 98.3%, average latency of 26 ms, average cost of 25.7%, authentication time 0.04 ms, multistep prediction’s MAPE, and RMSE values are 0.7645 and 0.9878 when compared to other popular methods.

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Acknowledgements

The authors are grateful to the Taif University Researchers Supporting Project number (TURSP-2020/36), Taif University, Taif, Saudi Arabia.

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Authors and Affiliations

  1. Department of Computer Science, College of Computers and Information Technology, Taif University, P. O. Box 11099, Taif, 21944, Saudi Arabia

    Roobaea Alroobaea

  2. School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology (VIT), Chennai Campus, Chennai, India

    Rajakumar Arul

  3. Department of Industrial and Systems Engineering, University of Jeddah, P.O. Box 80327, Jeddah, 21589, Saudi Arabia

    Saeed Rubaiee

  4. Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia

    Fahd S. Alharithi

  5. College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia

    Usman Tariq

  6. Shenzen Polytechnic, Shenzhen, 518055, People’s Republic of China

    Xincan Fan

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  1. Roobaea Alroobaea
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  2. Rajakumar Arul
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Correspondence to Xincan Fan.

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Alroobaea, R., Arul, R., Rubaiee, S. et al. AI-assisted bio-inspired algorithm for secure IoT communication networks. Cluster Comput 25, 1805–1816 (2022). https://doi.org/10.1007/s10586-021-03520-z

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  • DOI: https://doi.org/10.1007/s10586-021-03520-z

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