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In the rapidly evolving landscape of smart agriculture, guaranteeing the security and privacy of IoT sensor data is dominant. This paper presents a novel approach that integrates zero-knowledge proof (ZKP) mechanisms with IoT frameworks to improve data integrity while preserving privacy. Our methodology effectively addresses critical challenges such as data tampering, replay attacks, and data interception, significantly improving the overall security posture of agricultural datasets. Through rigorous testing, we verified that our approach not only mitigates possible security threats but also maintains high data utility. The results show a marked improvement in resistance to unauthorized access, with a 95.34% success rate in data validation and a 90.65% reduction in vulnerability to tampering compared to traditional methods. This study shows the superiority of our ZKP-based framework in providing a strong security solution modified for the unique demands of smart agriculture for safer and more reliable agricultural practices.

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A Zero-Knowledge Proof Approach on IoT Sensor Readings for Improving Data Security in Smart Agriculture

  • 会议论文

  • 发表日期：

    2026年

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  • Amit Chakraborty,
  • Sandip Roy,
  • Md. Morshed Alam,
  • Debasis Giri,
  • Sachin Shetty

摘要

In the rapidly evolving landscape of smart agriculture, guaranteeing the security and privacy of IoT sensor data is dominant. This paper presents a novel approach that integrates zero-knowledge proof (ZKP) mechanisms with IoT frameworks to improve data integrity while preserving privacy. Our methodology effectively addresses critical challenges such as data tampering, replay attacks, and data interception, significantly improving the overall security posture of agricultural datasets. Through rigorous testing, we verified that our approach not only mitigates possible security threats but also maintains high data utility. The results show a marked improvement in resistance to unauthorized access, with a 95.34% success rate in data validation and a 90.65% reduction in vulnerability to tampering compared to traditional methods. This study shows the superiority of our ZKP-based framework in providing a strong security solution modified for the unique demands of smart agriculture for safer and more reliable agricultural practices.