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Elsevier eBooks

Quantum cryptography for securing smart agriculture: A future-ready framework for data integrity and resilience

Shrabanti Kundu, Utpal Ghosh

Published Aug 14, 2026• 0 citations
Publisher
DOI
10.1016/b978-0-443-44247-6.00010-5

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•Feb 26, 2025•0 citations
The rapid growth of the Internet of Things (IoT) has connected billions of smart devices across healthcare, transportation, industrial automation, and smart home environments. While IoT has enhanced automation and data-driven decision-making, its widespread deployment has also increased the risk of cyberattacks. Conventional public-key cryptographic algorithms such as RSA and Elliptic Curve Cryptography (ECC) are vulnerable to future quantum computing attacks, particularly those based on Shor's algorithm. This paper proposes a Quantum-Resistant Cryptographic Framework (QRCF) for secure IoT communication using lattice-based cryptography integrated with lightweight authentication and efficient key management. The framework is designed to meet the computational limitations of IoT devices while ensuring long-term confidentiality and integrity. Performance evaluation demonstrates improvements in security resilience, authentication efficiency, and communication reliability compared with traditional cryptographic approaches. The proposed framework offers a scalable and future-ready solution for protecting IoT ecosystems in the post-quantum era.
Digital Twin (DT) technology, with Federated Learning (FL), enables decentralised and privacy-aware intelligence of large-scale infrastructures of smart cities. Quantum computing compromises the existing cryptography systems that underlie existing FL frameworks. The current paper presents a Quantum-Secure FL (QSec-FL) architecture that incorporates both Post-Quantum Cryptography (PQC) and Quantum Key Distribution (QKD) as methods to ensure quantum-resistant communication between the IoT, edge, and cloud layers of 6G networks. The framework facilitates real-time DT synchronisation and ultra-reliable low-latency communication (URLLC) through adaptive model aggregation and secure key management. With the help of a large dataset of SmartCity-6G-QSec, QSec-FL features better robustness, synchronisation integrity, and intrusion resilience than traditional secure FL systems. Additionally, the framework is compliant with the standards of NIST PQC, ETSI QKD, and 3GPP Release 19, ensuring compatibility and readiness for use in future 6G-based infrastructures. QSec-FL is a quantum-resilient security system incorporating federated intelligence to establish a unified, dependable, real-time DT operation and safe AI-based decision-making of the advanced smart cities.
Abstract: The increasing global demand for food, coupled with the challenges of climate change, resource scarcity, and supply chain inefficiencies, necessitates transformative solutions in agriculture and food security. Traditional AI-driven agricultural systems, while effective, often struggle with processing vast, complex, and interdependent variables such as weather patterns, soil quality, pest outbreaks, and logistics optimization. Quantum AI, which merges the computational power of quantum computing and artificial intelligence, offers unprecedented capabilities in predictive analytics, real-time decision-making, and optimization for sustainable farming. This chapter explores Quantum AI’s applications in precision agriculture, climate-resilient farming, pest and disease prediction, and smart food supply chains, demonstrating how quantum-enhanced models optimize irrigation, enhance crop yield forecasts, and improve food distribution efficiency. Additionally, it highlights the challenges, ethical considerations, and future potential of Quantum AI in ensuring global food security while promoting environmental sustainability. By integrating Quantum AI with IoT, blockchain, and remote sensing technologies, this chapter outlines a strategic roadmap for transforming agriculture into a highly efficient, adaptive, and climate-resilient system, paving the way for a food-secure and ecologically sustainable future. Keywords: Quantum AI, food security, sustainable agriculture, precision farming, climate-resilient farming, quantum computing in agriculture, smart food supply chains, predictive analytics, crop yield optimization, pest and disease prediction, quantum-enhanced logistics, irrigation management, AI-driven agriculture, blockchain for food traceability, sustainable resource management, quantum optimization algorithms