STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal Of Network security Review Article

Digital Agriculture Schemes in Kerala: Risk Analysis and Multi-Layered Security Framework

  1. Sreekala K.M. Department of Management, Padmashree Institute of Management and Sciences, Bangalore
  2. Thara Chakkingal Department of Management, Thakur Institute of Management Studies, Career Development and Research, Mumbai

Abstract

Kerala’s agricultural sector is undergoing rapid digital transformation, driven by initiatives such as the e-Krishi platform and the growing adoption of Internet of Things (IoT)–enabled precision farming technologies. While these developments promise improved productivity, transparency, and data-driven decision-making, they also introduce significant cybersecurity and data governance challenges that cannot be overlooked. This paper critically examines the emerging security, privacy, and operational risks associated with the digitization of agricultural services in Kerala. Attention is given to the vulnerability of data integrity, the risks arising from low levels of digital literacy among farmers, and the often-underestimated threat of insider misuse within digital systems. Through a structured assessment, the study systematically identifies and ranks key security and operational threats that could undermine the reliability and trustworthiness of digital agriculture platforms. If dynamic agricultural data remains inadequately protected, or if farmers lack meaningful control over how their data is collected, shared, and used, the long-term growth of the sector may be compromised, and public trust significantly eroded. To address these concerns, the paper proposes a novel multi-layered security and data governance framework (M-LSF) tailored for resource-constrained environments. The framework integrates a strong policy foundation centered on farmer data sovereignty with practical, cost-effective technological safeguards. These include lightweight cryptographic mechanisms, role-based access controls, and artificial intelligence (AI)/machine learning (ML) driven anomaly detection to identify suspicious activities in real time. By combining governance principles with advanced yet scalable security controls, the M-LSF aims to safeguard farmer privacy, protect sensitive agricultural data, and strengthen institutional resilience, thereby enabling Kerala to pursue sustainable and trustworthy digital agriculture.

Keywords

References (38)

  1. Gyamfi EK, ElSayed Z, Kropczynski J, Yakubu MA, Elsayed N. Agricultural 4.0 Leveraging on Technological Solutions: Study for Smart Farming Sector. 2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI). 2024:1-9. doi:10.1109/icmi60790.2024.10585910
  2. Das M. National Bank for Agriculture and Rural Development (NABARD). International Journal of Research and Review. 2021;8(12):75-82. doi:10.52403/ijrr.20211211
  3. Vardhan R, Kumar R, Supraja P. Intelligent Fortification of Agricultural Data Integrity. 2024 2nd International Conference on Networking and Communications (ICNWC). 2024:1-8. doi:10.1109/icnwc60771.2024.10537380
  4. Ahmed B, Shabbir H, Naqvi SR, Peng L. Smart Agriculture: Current State, Opportunities, and Challenges. IEEE Access. 2024;12:144456-144478. doi:10.1109/access.2024.3471647
  5. Islam MH, Anam MZ, Hoque MR, Nishat M, Bari ABMM. Agriculture 4.0 adoption challenges in the emerging economies: Implications for smart farming and sustainability. Journal of Economy and Technology. 2024;2:278-295. doi:10.1016/j.ject.2024.09.002
  6. Hota J, Verma VK. Challenges to Adoption of Digital Agriculture in India. 2022 International Conference on Maintenance and Intelligent Asset Management (ICMIAM). 2022:1-6. doi:10.1109/icmiam56779.2022.10147002
  7. Adebunmi Okechukwu Adewusi, Njideka Rita Chiekezie, Nsisong Louis Eyo-Udo. Cybersecurity in precision agriculture: Protecting data integrity and privacy. International Journal of Applied Research in Social Sciences. 2023;5(10):693-708. doi:10.51594/ijarss.v5i10.1482
  8. Nodehi NR, Berisha F, Da Silva L, Pourzolfaghar Z, Helfert M. Integrating Cybersecurity, Data Sovereignty and Trustworthiness in Agri-data Sharing Environments: A Conceptual Framework. 2024 Cyber Research Conference - Ireland (Cyber-RCI). 2024:1-8. doi:10.1109/cyber-rci60769.2024.10939388
  9. Malhotra H, Bhargava R, Dave M. Challenges related to information security and its implications for evolving e-government structures: A comparative study between India and African countries. 2017 International Conference on Inventive Computing and Informatics (ICICI). 2017:30-35. doi:10.1109/icici.2017.8365370
  10. Hasan A, Hashem MMA. A Lightweight Cryptographic Framework Based on Hybrid Cellular Automata for IoT Applications. IEEE Access. 2024;12:192672-192688. doi:10.1109/access.2024.3519673
  11. Nagarajan S, Vijay S, Karthi S, Praveen R, Vijaya Babu K R, Naresh B. Enhancing IoT-Based Smart Farming Security with a Hybrid GRU Intrusion Detection System. 2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI). 2025:1-6. doi:10.1109/iatmsi64286.2025.10985129
  12. Thakor VA, Razzaque MA, Khandaker MRA. Lightweight Cryptography Algorithms for Resource-Constrained IoT Devices: A Review, Comparison and Research Opportunities. IEEE Access. 2021;9:28177-28193. doi:10.1109/access.2021.3052867
  13. Dargaoui S, Azrour M, El Allaoui A, Guezzaz A, Benkirane S, Alabdulatif A, et al. IoT-Driven Smart Agriculture: Security Issues and Authentication Schemes Classification. Lecture Notes in Networks and Systems. 2024:61-66. doi:10.1007/978-3-031-70411-6_10
  14. Kristen E, Kloibhofer R, Díaz VH, Castillejo P. Security Assessment of Agriculture IoT (AIoT) Applications. Applied Sciences. 2021;11(13):5841. doi:10.3390/app11135841
  15. Udisha O, Ambily Philomina IG. Bridging the Digital Divide: Empowering Rural Women Farmers Through Mobile Technology in Kerala. Sustainability. 2024;16(21):9188. doi:10.3390/su16219188
  16. Adebunmi Okechukwu Adewusi, Njideka Rita Chiekezie, Nsisong Louis Eyo-Udo. Cybersecurity in precision agriculture: Protecting data integrity and privacy. International Journal of Applied Research in Social Sciences. 2023;5(10):693-708. doi:10.51594/ijarss.v5i10.1482
  17. Bissadu K, Hossain G, Velagala LP, Sonko S. Analyzing Insider Cyber Threats and Human Factors within the Framework of Agriculture 5.0. 2024 12th International Symposium on Digital Forensics and Security (ISDFS). 2024:1-5. doi:10.1109/isdfs60797.2024.10527290
  18. Manwatkar AB, Keshavrao Deshmukh R, Junnarkar AA, Jagdish Kamble S, Kachare PK, Prashant Latkar S. Securing Industry 4.0-Based Precision Agriculture. 2024 IEEE 4th International Conference on ICT in Business Industry & Government (ICTBIG). 2024:1-7. doi:10.1109/ictbig64922.2024.10911640
  19. Alahmadi AN, Rehman SU, Alhazmi HS, Glynn DG, Shoaib H, Solé P. Cyber-Security Threats and Side-Channel Attacks for Digital Agriculture. Sensors. 2022;22(9):3520. doi:10.3390/s22093520
  20. Naseer A, Shmoon M, Shakeel T, Ur Rehman S, Ahmad A, Gruhn V. A Systematic Literature Review of the IoT in Agriculture—Global Adoption, Innovations, Security, and Privacy Challenges. IEEE Access. 2024;12:60986-61021. doi:10.1109/access.2024.3394617
  21. Abbasi M, Plaza-Hernandez M, Prieto J, Corchado JM. Security in the Internet of Things Application Layer: Requirements, Threats, and Solutions. IEEE Access. 2022;10:97197-97216. doi:10.1109/access.2022.3205351
  22. Jung N, Kang H, Li L, Choi W. Building a Crop Environmental Data Monitoring System Using Blockchain-Based Smart Contracts. 2024 IEEE 13th Global Conference on Consumer Electronics (GCCE). 2024:1340-1341. doi:10.1109/gcce62371.2024.10760591
  23. Elbasi E, Mostafa N, AlArnaout Z, Zreikat AI, Cina E, Varghese G, et al. Artificial Intelligence Technology in the Agricultural Sector: A Systematic Literature Review. IEEE Access. 2023;11:171-202. doi:10.1109/access.2022.3232485
  24. Bica I, Chifor BC, Arseni ȘC, Matei I. Multi-Layer IoT Security Framework for Ambient Intelligence Environments. Sensors. 2019;19(18):4038. doi:10.3390/s19184038
  25. Amiri-Zarandi M, Dara RA, Duncan E, Fraser EDG. Big Data Privacy in Smart Farming: A Review. Sustainability. 2022;14(15):9120. doi:10.3390/su14159120
  26. von Lautz-Cauzanet E. e-Krishi: The online platform for small farmers (India). In: Zeng H, Xia W, Wang J, Wang R, editors. Approach of ICT in education for rural development: Good practices from developing countries. New Delhi: SAGE Publications; 2015. p. 342–366.
  27. Gans Combe C, Camaréna S. Data sovereignty and valuation model for sustainable agriculture innovation and equity. npj Sustainable Agriculture. 2025;3(1). doi:10.1038/s44264-025-00102-z
  28. J MP, Fallah MH, Meenakshi, Hemamalini M, Saranya NN. Threat Detection for IoT-Based Smart Farming Systems Based on Bidirectional Gated Recurrent Unit with Long Short-Term Memory. 2024 4th International Conference on Mobile Networks and Wireless Communications (ICMNWC). 2024:1-5. doi:10.1109/icmnwc63764.2024.10872064
  29. Alanazi B, Alrashdi I. Anomaly Detection in Smart Agriculture Systems on Network Edge Using Deep Learning Technique. Sustainable Machine Intelligence Journal. 2023;3. doi:10.61185/smij.2023.33104
  30. Janssen SJC, Porter CH, Moore AD, Athanasiadis IN, Foster I, Jones JW, et al. Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology. Agricultural Systems. 2017;155:200-212. doi:10.1016/j.agsy.2016.09.017
  31. Sharma K, Shivandu SK. Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture. Sensors International. 2024;5:100292. doi:10.1016/j.sintl.2024.100292
  32. Singhal G, Singh A. Probabilistic Data Structure in smart agriculture. 2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC). 2023:780-785. doi:10.1109/icsccc58608.2023.10176985
  33. Chakraborty S, Choudhury N, Kalita I. AI‐Based Smart Agriculture Monitoring Using Ground‐Based and Remotely Sensed Images. The New Advanced Society. 2022:191-221. doi:10.1002/9781119884392.ch9
  34. Demestichas K, Peppes N, Alexakis T, Adamopoulou E. Blockchain in Agriculture Traceability Systems: A Review. Applied Sciences. 2020;10(12):4113. doi:10.3390/app10124113
  35. NITI Aayog. National Strategy for Artificial Intelligence. New Delhi: Government of India; 2018.
  36. Kasyapa MS, C V. A Privacy Protection Mechanism for Indian Health Care Data Exchange Using Blockchain. 2023 Innovations in Power and Advanced Computing Technologies (i-PACT). 2023:1-9. doi:10.1109/i-pact58649.2023.10434770
  37. Zafar O, González RS, Namazi M, Morales A, Ayday E. Empowering digital agriculture: A privacy-preserving framework for data sharing and collaborative research. [Preprint]. 2025. arXiv:2506.20872. doi:10.48550/arXiv.2506.20872.
  38. Ada Lovelace Institute. Exploring Legal Mechanisms for Data Stewardship: Working Group Final Report. London: Ada Lovelace Institute; 2021. Available from: https://www.adalovelaceinstitute.org/report/legal-mechanisms-data-stewardship/
Support