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A Secure Behavior Modelling for IoT Networks Using Blockchain: Blockchain-Based Reputation-Based Agent Grouping in the Internet of Things
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Author(s): Jameel Ahmad Qurashi (Poornima University, India), Vikram Singh (Poornima University, India), Bright Keswani (Poornima University, India), Saurabh Shandilya (Poornima College of Engineering, Poornima University, India), Adarsh Kumar Pandey (Poornima University, India)and Shikha Sharma (Poornima University, India)
Copyright: 2025
Pages: 36
Source title:
Internet of Behavior-Based Computational Intelligence for Smart Education Systems
Source Author(s)/Editor(s): Mariya Ouaissa (Cadi Ayyad University, Morocco), Mariyam Ouaissa (Chouaib Doukkali University, Morocco), Hanane Lamaazi (College of Information Technology, UAE University, UAE), Mahmoud El Hamlaoui (Mohammed V University, Morocco)and Kishor Kumar Reddy C. (Stanley College of Engineering and Technology for Women, India)
DOI: 10.4018/979-8-3693-8151-9.ch012
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Abstract
The Internet of Things (IoT) lets smart devices and humans use enticing services. Fostering adaptive machine-to-machine cooperation among intelligent objects may help IoT devices reach powerful sensing, reasoning, and real-time acting capabilities. To employ multiagent systems and the social attitude of engaging and cooperating for services, IoT devices must be paired with software agents. As IoT devices move across numerous settings, it may be challenging to locate credible partners for cooperation. As reputation may affect social groups, grouping agents in each IoT environment by social skills may be a solution. This study emphasizes agent reputation capital in a reputation model. Second, reputation capital organized IoT agents. The last contribution is employing blockchain technology to authenticate reputation capital, because this competition needs trustworthy and verified device or agent reputation information. Our testing shows that the model can identify almost all deceptive agents and provide good group composition findings if their proportion is below a threshold.
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