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Paper ID:IJSREM64993

BLOCKCHAIN-ENABLED IOT DEVICE FOR LIGHTWEIGHT MESSAGE AUTHENTICATION IN INDUSTRIAL APPLICATION

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM64993

Volume:

10 |

6 |

Jun 2026

Pages:

1-7

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM64993

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GPJ

Geetha Priya J

Department of Computer Science and Engineering

R.M.D. Engineering College.

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CBS

CH Bala Subramanyam

Department of Computer Science and Engineering

R.M.D. Engineering College.

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GMSK

G Muni Sai Kethan

Department of Computer Science and Engineering

R.M.D. Engineering College.

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GDR

G Dhanush Reddy

Department of Computer Science and Engineering

R.M.D. Engineering College.

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Abstract

In the rapidly evolving industrial landscape, secure and efficient data exchange is essential for operational reliability and regulatory compliance. Traditional monitoring methods, reliant on manual inspections, often lead to delayed fault detection, increased downtime, and heightened safety risks. To address these challenges, the integration of blockchain and the Internet of Things (IoT) presents a transformative solution for real-time industrial monitoring with lightweight message authentication. This paper proposes a blockchain-enabled IoT framework for secure and efficient monitoring of critical parameters such as temperature, gas emissions, and machine vibrations. By leveraging IoT-enabled smart sensors, real-time data is continuously collected and transmitted through a decentralized blockchain network, ensuring tamper-proof authentication and preventing unauthorized access. The integration of blockchain enhances data integrity, mitigates security vulnerabilities, and provides transparent, verifiable records for compliance and predictive maintenance. Through a secure web dashboard or mobile application, industry managers gain remote access to real-time insights, enabling proactive decision-making and reducing unforeseen equipment failures. This approach not only enhances operational efficiency but also establishes a robust, trust-driven ecosystem for industrial automation. By combining the strengths of blockchain and IoT, this system redefines security, efficiency, and reliability in industrial applications.

KEYWORDS

Blockchain IoT platform equipment supervision Smart supply chain management AES Algorithm self-sovereign identity Hyperledger.

Cite This Article

Geetha Priya J, CH Bala Subramanyam, G Muni Sai Kethan, G Dhanush Reddy, "BLOCKCHAIN-ENABLED IOT DEVICE FOR LIGHTWEIGHT MESSAGE AUTHENTICATION IN INDUSTRIAL APPLICATION," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-7, Jun 2026. https://doi.org/10.55041/IJSREM64993

Full Article/Conclusion

  The IoT-enabled industrial monitoring system enhances safety and efficiency by integrating sensors for real-time risk detection and maintenance, minimizing downtime and boosting productivity. A key application is hazardous gas detection, crucial for preventing industrial accidents. Its IoT-based design ensures cost-effectiveness, scalability, and adaptability across industries. The system also incorporates blockchain security, providing high data integrity and reliability. Experimental results show 40% lower latency, zero transaction costs, and 100% fake sensor prevention.   Additionally, its ability to provide continuous updates supports informed decision-making, fostering a more resilient and sustainable industrial environment. The system’s scalability allows seamless integration across various industrial domains, ensuring widespread adoption. With its combination of IoT, blockchain, and real-time monitoring, it not only enhances security but also drives ongoing research and innovation in industrial safety technologies, shaping the future of smart industries.

References

[1] Z. Yong, Z. Liyi, H. Jianfeng, B. Zhe and Y. Yi, “An indoor gas leakage source localization algorithm using distributed maximum likelihood estimation in sensor networks,” Springer - Journal of Ambient Intelligence and Humanized Computing, vol. 10, pp. 1703–1712, November 2017.   [2] Hongwei Li, Haoyang Li, H. Pei and Z. Li, “Leakage detection of HVAC pipeline network based on pressure signal diagnosis,” Springer -Building Simulation, vol. 12, pp. 617–628, June 2019.   [3] Knowles W, Prince D, Hutchison D, et al. A survey of cyber security management in industrial control systems[J]. International journal of critical infrastructure protection, 2015, 9: 52-80.   [4] Macaulay T, Singer B L. Cybersecurity for industrial control systems: SCADA, DCS, PLC, HMI, and SIS[M]. Auerbach Publications, 2016.   [5] Sankalp Raghuvanshi, Kalpana Singh, “Light Fidelity: The Future of Data Communication,” International Journal of Engineering Research & Technology, 2020,9.   [6] R. Mahendran, “Integrated Li-Fi (Light Fidelity) For Smart Communication through Illumination,” IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT), 2016, 53-56.   [7] R. A. Ramlee, M. A. Othman, M. H. Leong, M. M. Ismail and S. S. S. Ranjit, "Smart home system using android application," Information and Communication Technology (ICoICT), 2013 International Conference of, Bandung, 2013, pp. 277-280.   [8] M. Asadullah and A. Raza, "An overview of home automation systems," 2016 2nd International Conference on Robotics and Artificial Intelligence (ICRAI), Rawalpindi, 2016, pp. 27-31, doi: 10.1109/ICRAI.2016.7791223.   [9] ZHU Qing,LI Yan-ping. The Design of sensing system of mechanical  assembly line based on Internet of things [J]. Information Technology &Informatization, 2018, 225(12):133-136.   [10] KANG Cheng-bo, YANG Hui-bin, YAN Juan, et al. Remote Control and Monitoring System Based on IOT Industrial Robots[J]. Control and Instruments in Chemical Industry, 2019, 046(005):367-370.

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Publication Date

6/16/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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