IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i9p2073-d1134324.html
   My bibliography  Save this article

Enhancing Data Security in IoT Networks with Blockchain-Based Management and Adaptive Clustering Techniques

Author

Listed:
  • Ajmeera Kiran

    (Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad 500043, India)

  • Prasad Mathivanan

    (School of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, India)

  • Miroslav Mahdal

    (Department of Control Systems and Instrumentation, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70800 Ostrava, Czech Republic)

  • Kanduri Sairam

    (Department of Electronics and Communication Engineering, NITTE Deemed to Be University, Udupi 574110, India)

  • Deepak Chauhan

    (School of Computing, Graphic Era Hill University, Dehradun 248002, India
    Graphic Era Deemed to Be University, Dehradun 248002, India)

  • Vamsidhar Talasila

    (Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur 522502, India)

Abstract

The rapid proliferation of smart devices in Internet of Things (IoT) networks has amplified the security challenges associated with device communications. To address these challenges in 5G-enabled IoT networks, this paper proposes a multi-level blockchain security architecture that simplifies implementation while bolstering network security. The architecture leverages an adaptive clustering approach based on Evolutionary Adaptive Swarm Intelligent Sparrow Search (EASISS) for efficient organization of heterogeneous IoT networks. Cluster heads (CH) are selected to manage local authentication and permissions, reducing overhead and latency by minimizing communication distances between CHs and IoT devices. To implement network changes such as node addition, relocation, and deletion, the Network Efficient Whale Optimization (NEWO) algorithm is employed. A localized private blockchain structure facilitates communication between CHs and base stations, providing an authentication mechanism that enhances security and trustworthiness. Simulation results demonstrate the effectiveness of the proposed clustering algorithm compared to existing methodologies. Overall, the lightweight blockchain approach presented in this study strikes a superior balance between network latency and throughput when compared to conventional global blockchain systems. Further analysis of system under test (SUT) behavior was accomplished by running many benchmark rounds at varying transaction sending speeds. Maximum, median, and lowest transaction delays and throughput were measured by generating 1000 transactions for each benchmark. Transactions per second (TPS) rates varied between 20 and 500. Maximum delay rose when throughput reached 100 TPS, while minimum latency maintained a value below 1 s.

Suggested Citation

  • Ajmeera Kiran & Prasad Mathivanan & Miroslav Mahdal & Kanduri Sairam & Deepak Chauhan & Vamsidhar Talasila, 2023. "Enhancing Data Security in IoT Networks with Blockchain-Based Management and Adaptive Clustering Techniques," Mathematics, MDPI, vol. 11(9), pages 1-14, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:2073-:d:1134324
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/9/2073/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/9/2073/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Seonghyeon Gong & Erzhena Tcydenova & Jeonghoon Jo & Younghun Lee & Jong Hyuk Park, 2019. "Blockchain-Based Secure Device Management Framework for an Internet of Things Network in a Smart City," Sustainability, MDPI, vol. 11(14), pages 1-17, July.
    2. Fu, Xiuwen & Yao, Haiqing & Yang, Yongsheng, 2019. "Modeling and analyzing cascading dynamics of the clustered wireless sensor network," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 1-10.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Baoshan Xie & Fei Li & Hao Li & Liya Wang & Aimin Yang, 2023. "Enhanced Internet of Things Security Situation Assessment Model with Feature Optimization and Improved SSA-LightGBM," Mathematics, MDPI, vol. 11(16), pages 1-15, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiuwen Fu & Haiqing Yao & Yongsheng Yang, 2019. "Sink-Convergence Cascading Model for Wireless Sensor Networks with Different Load-Redistribution Schemes," Complexity, Hindawi, vol. 2019, pages 1-9, June.
    2. Geng, Sunyue & Liu, Sifeng & Fang, Zhigeng & Gao, Su, 2021. "A reliable framework for satellite networks achieving energy requirements," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    3. Abderahman Rejeb & Karim Rejeb & Steven J. Simske & John G. Keogh, 2022. "Blockchain technology in the smart city: a bibliometric review," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 2875-2906, October.
    4. Fu, Xiuwen & Li, Qing & Li, Wenfeng, 2023. "Modeling and analysis of industrial IoT reliability to cascade failures: An information-service coupling perspective," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    5. Fernando Almeida, 2023. "Prospects of Cybersecurity in Smart Cities," Future Internet, MDPI, vol. 15(9), pages 1-21, August.
    6. Li Zhao & Zhi-ying Tang & Xin Zou, 2019. "Mapping the Knowledge Domain of Smart-City Research: A Bibliometric and Scientometric Analysis," Sustainability, MDPI, vol. 11(23), pages 1-28, November.
    7. Geng, Sunyue & Liu, Sifeng & Fang, Zhigeng & Gao, Su, 2021. "An agent-based clustering framework for reliable satellite networks," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    8. Dejian Yu & Libo Sheng, 2020. "Knowledge diffusion paths of blockchain domain: the main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 471-497, October.
    9. Fu, Xiuwen & Yang, Yongsheng, 2020. "Modeling and analysis of cascading node-link failures in multi-sink wireless sensor networks," Reliability Engineering and System Safety, Elsevier, vol. 197(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:2073-:d:1134324. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.