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Sustainable Network by Enhancing Attribute-Based Selection Mechanism Using Lagrange Interpolation

Author

Listed:
  • Chetna Monga

    (Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India)

  • Deepali Gupta

    (Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India)

  • Devendra Prasad

    (Department of Computer Science and Engineering, Panipat Institute of Engineering & Technology (PIET), Samalkha, Panipat 132102, Haryana, India)

  • Sapna Juneja

    (Department of Computer Science, KIET Group of Institutions, Delhi NCR, Ghaziabad 201206, Uttar Pradesh, India)

  • Ghulam Muhammad

    (Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)

  • Zulfiqar Ali

    (School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK)

Abstract

The security framework in Ad-hoc Networks (ANET) continues to attract the attention of researchers, although significant work has been accomplished already. Researchers in the last couple of years have shown quite an improvement in Identity Dependent Cryptography (IDC). Security in ANET is hard to attain due to the vulnerability of links (Wireless). IDC encompasses Polynomial Interpolations (PI) such as Lagrange, curve-fitting, and spline to provide security by implementing Integrated Key Management (IKM). The PI structure trusts all the available nodes in the network and randomly picks nodes for the security key generation. This paper presents a solution to the trust issues raised in Lagrange’s-PI (LI) utilizing an artificial neural network and attribute-based tree structure. The proposed structure not only improves the trust factor but also enhances the accuracy measures of LI to provide a sustainable network system. Throughput, PDR, noise, and latency have been increased by 47%, 50%, 34%, and 30%, respectively, by using LI and incorporating the aforementioned techniques.

Suggested Citation

  • Chetna Monga & Deepali Gupta & Devendra Prasad & Sapna Juneja & Ghulam Muhammad & Zulfiqar Ali, 2022. "Sustainable Network by Enhancing Attribute-Based Selection Mechanism Using Lagrange Interpolation," Sustainability, MDPI, vol. 14(10), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6082-:d:817409
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    References listed on IDEAS

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    1. Kamran Shaukat & Suhuai Luo & Vijay Varadharajan & Ibrahim A. Hameed & Shan Chen & Dongxi Liu & Jiaming Li, 2020. "Performance Comparison and Current Challenges of Using Machine Learning Techniques in Cybersecurity," Energies, MDPI, vol. 13(10), pages 1-27, May.
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    Cited by:

    1. Mudita Uppal & Deepali Gupta & Sapna Juneja & Adel Sulaiman & Khairan Rajab & Adel Rajab & M. A. Elmagzoub & Asadullah Shaikh, 2022. "Cloud-Based Fault Prediction for Real-Time Monitoring of Sensor Data in Hospital Environment Using Machine Learning," Sustainability, MDPI, vol. 14(18), pages 1-19, September.

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