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Enhancing Blockchain Transaction Validation in Wireless Sensor Networks Using Random Forests


Affiliations
1 Department of Computer Science and Engineering, Chettinad College of Engineering and Technology, India
2 Department of Computer Science and Engineering, Kamla Nehru Institute of Physical and Social Sciences, India
3 Department of Computer Engineering, Vasantdada Patil Pratishthan College of Engineering and Visual Arts, India
4 Department of Electronics and Communication Engineering, KSK college of Engineering and Technology, India
     

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As a distributed and decentralized ledger that ensures secure and transparent transactions, blockchain technology has attracted considerable interest. In the context of wireless sensor networks (WSNs), where nodes with limited resources conduct transactions, ensuring efficient and trustworthy validation becomes a challenge. Using random forests, this paper proposes a novel method for enhancing blockchain transaction validation in WSNs. The proposed method enhances the accuracy and efficiency of transaction validation in WSNs by leveraging the ensemble-learning capabilities of random forests. The random forests model is trained with transaction content, originating node information, and network metrics extracted from WSN transactions. Experimental results indicate that the proposed method improves transaction validation precision and decreases validation time in comparison to conventional methods. In addition, the random forests model is resistant to multiple types of attacks, assuring the security and integrity of WSN transactions. The results demonstrate that random forests are a promising technique for improving blockchain transaction validation in wireless sensor networks.

Keywords

Blockchain, Wireless Sensor Networks, Transaction Validation, Random Forests, Ensemble Learning, Resource-Constrained Nodes, Security, Integrity, Efficiency, Decentralized Ledger, Ensemble Learning.
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  • Enhancing Blockchain Transaction Validation in Wireless Sensor Networks Using Random Forests

Abstract Views: 125  |  PDF Views: 0

Authors

T. Gobinath
Department of Computer Science and Engineering, Chettinad College of Engineering and Technology, India
Sanjay Kumar Sonkar
Department of Computer Science and Engineering, Kamla Nehru Institute of Physical and Social Sciences, India
Vinod N. Alone
Department of Computer Engineering, Vasantdada Patil Pratishthan College of Engineering and Visual Arts, India
C. Thiripurasundari
Department of Electronics and Communication Engineering, KSK college of Engineering and Technology, India

Abstract


As a distributed and decentralized ledger that ensures secure and transparent transactions, blockchain technology has attracted considerable interest. In the context of wireless sensor networks (WSNs), where nodes with limited resources conduct transactions, ensuring efficient and trustworthy validation becomes a challenge. Using random forests, this paper proposes a novel method for enhancing blockchain transaction validation in WSNs. The proposed method enhances the accuracy and efficiency of transaction validation in WSNs by leveraging the ensemble-learning capabilities of random forests. The random forests model is trained with transaction content, originating node information, and network metrics extracted from WSN transactions. Experimental results indicate that the proposed method improves transaction validation precision and decreases validation time in comparison to conventional methods. In addition, the random forests model is resistant to multiple types of attacks, assuring the security and integrity of WSN transactions. The results demonstrate that random forests are a promising technique for improving blockchain transaction validation in wireless sensor networks.

Keywords


Blockchain, Wireless Sensor Networks, Transaction Validation, Random Forests, Ensemble Learning, Resource-Constrained Nodes, Security, Integrity, Efficiency, Decentralized Ledger, Ensemble Learning.

References