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Blockchain-Based Cloud-Enabled Security Monitoring Using Internet of Things in Smart Agriculture

Author

Listed:
  • Rajasekhar Chaganti

    (Toyota Research Institute, Los Altos, CA 94022, USA)

  • Vijayakumar Varadarajan

    (School of Computer Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia
    School of NUOVOS, Ajeenkya DY Patil University, Pune 412105, India)

  • Venkata Subbarao Gorantla

    (Software Developer, Victorville, CA 92395, USA)

  • Thippa Reddy Gadekallu

    (Department of Information Technology, VIT University, Vellore 632014, India)

  • Vinayakumar Ravi

    (Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar 31952, Saudi Arabia)

Abstract

The Internet of Things (IoT) has rapidly progressed in recent years and immensely influenced many industries in how they operate. Consequently, IoT technology has improved productivity in many sectors, and smart farming has also hugely benefited from the IoT. Smart farming enables precision agriculture, high crop yield, and the efficient utilization of natural resources to sustain for a longer time. Smart farming includes sensing capabilities, communication technologies to transmit the collected data from the sensors, and data analytics to extract meaningful information from the collected data. These modules will enable farmers to make intelligent decisions and gain profits. However, incorporating new technologies includes inheriting security and privacy consequences if they are not implemented in a secure manner, and smart farming is not an exception. Therefore, security monitoring is an essential component to be implemented for smart farming. In this paper, we propose a cloud-enabled smart-farm security monitoring framework to monitor device status and sensor anomalies effectively and mitigate security attacks using behavioral patterns. Additionally, a blockchain-based smart-contract application was implemented to securely store security-anomaly information and proactively mitigate similar attacks targeting other farms in the community. We implemented the security-monitoring-framework prototype for smart farms using Arduino Sensor Kit, ESP32, AWS cloud, and the smart contract on the Ethereum Rinkeby Test Network and evaluated network latency to monitor and respond to security events. The performance evaluation of the proposed framework showed that our solution could detect security anomalies within real-time processing time and update the other farm nodes to be aware of the situation.

Suggested Citation

  • Rajasekhar Chaganti & Vijayakumar Varadarajan & Venkata Subbarao Gorantla & Thippa Reddy Gadekallu & Vinayakumar Ravi, 2022. "Blockchain-Based Cloud-Enabled Security Monitoring Using Internet of Things in Smart Agriculture," Future Internet, MDPI, vol. 14(9), pages 1-20, August.
    • Handle: RePEc:gam:jftint:v:14:y:2022:i:9:p:250-:d:896406
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    References listed on IDEAS

    as
    1. Chunling Li & Ben Niu, 2020. "Design of smart agriculture based on big data and Internet of things," International Journal of Distributed Sensor Networks, , vol. 16(5), pages 15501477209, May.
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    Cited by:

    1. Rajasekhar Chaganti & Azrour Mourade & Vinayakumar Ravi & Naga Vemprala & Amit Dua & Bharat Bhushan, 2022. "A Particle Swarm Optimization and Deep Learning Approach for Intrusion Detection System in Internet of Medical Things," Sustainability, MDPI, vol. 14(19), pages 1-18, October.
    2. Sharnil Pandya & Thippa Reddy Gadekallu & Praveen Kumar Reddy Maddikunta & Rohit Sharma, 2022. "A Study of the Impacts of Air Pollution on the Agricultural Community and Yield Crops (Indian Context)," Sustainability, MDPI, vol. 14(20), pages 1-17, October.

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