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A Trust-Based Predictive Model for Mobile Ad Hoc Network in Internet of Things
Waleed Alnumay1, Uttam Ghosh2, Pushpita Chatterjee3
1Computer Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia. wnumay@ksu.edu.sa.
Sensors (Basel, Switzerland)
|March 29, 2019
Summary
This study introduces a new trust model for the Internet of Things (IoT) within mobile ad hoc networks (MANETs). The model enhances security and reliability by evaluating node trustworthiness for efficient data routing.
Area of Science:
- Computer Science
- Network Security
Background:
- The Internet of Things (IoT) integrates diverse wireless networks like WSNs, ZigBee, Wi-Fi, MANETs, and RFID.
- Ensuring IoT compatibility with WSNs and MANETs is crucial for smart environments and user adoption.
Purpose of the Study:
- To propose a novel quantitative trust model tailored for IoT-MANET environments.
- To enhance the security and reliability of data transmission in heterogeneous IoT networks.
Main Methods:
- A quantitative trust model combining direct and indirect trust opinions.
- Utilizing Beta probabilistic distribution to integrate trust evidence and calculate direct trust.
- Employing ARMA/GARCH theory for combining recommendation trust and multi-step ahead trust prediction.
- Designing a secure routing protocol prioritizing trustworthy nodes.
Main Results:
- The proposed trust model effectively combines direct and indirect trust metrics.
- ARMA/GARCH successfully predicts future trust values for nodes.
- The developed routing protocol ensures secure and reliable packet delivery.
- Simulation results demonstrate superior performance compared to existing trust models.
Conclusions:
- The novel trust model significantly improves security and reliability in IoT-MANETs.
- The integration of direct and indirect trust, along with advanced prediction techniques, offers a robust solution.
- The findings support the development of more trustworthy and efficient IoT ecosystems.
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