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Logistic Regression Trust–A Trust Model for Internet-of-Things Using Regression Analysis

Feslin Anish Mon Solomon1,*, Godfrey Winster Sathianesan2, R. Ramesh3

1 Department of CSE, Saveetha Engineering College, Chennai, India
2 Department of CSE, SRM Institute of Science and Technology, Chennai, India
3 Department of ECE, Saveetha Engineering College, Chennai, India

* Corresponding Author: Feslin Anish Mon Solomon. Email: email

Computer Systems Science and Engineering 2023, 44(2), 1125-1142.


Internet of Things (IoT) is a popular social network in which devices are virtually connected for communicating and sharing information. This is applied greatly in business enterprises and government sectors for delivering the services to their customers, clients and citizens. But, the interaction is successful only based on the trust that each device has on another. Thus trust is very much essential for a social network. As Internet of Things have access over sensitive information, it urges to many threats that lead data management to risk. This issue is addressed by trust management that help to take decision about trustworthiness of requestor and provider before communication and sharing. Several trust-based systems are existing for different domain using Dynamic weight method, Fuzzy classification, Bayes inference and very few Regression analysis for IoT. The proposed algorithm is based on Logistic Regression, which provide strong statistical background to trust prediction. To make our stand strong on regression support to trust, we have compared the performance with equivalent sound Bayes analysis using Beta distribution. The performance is studied in simulated IoT setup with Quality of Service (QoS) and Social parameters for the nodes. The proposed model performs better in terms of various metrics. An IoT connects heterogeneous devices such as tags and sensor devices for sharing of information and avail different application services. The most salient features of IoT system is to design it with scalability, extendibility, compatibility and resiliency against attack. The existing works finds a way to integrate direct and indirect trust to converge quickly and estimate the bias due to attacks in addition to the above features.


Cite This Article

F. Anish Mon Solomon, G. Winster Sathianesan and R. Ramesh, "Logistic regression trust–a trust model for internet-of-things using regression analysis," Computer Systems Science and Engineering, vol. 44, no.2, pp. 1125–1142, 2023.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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