An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer

Shanzhen Gao; Weizheng Gao; Ephrem Eyob; Ju Hyeong Jin

An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer

Abstract

Smart agriculture increasingly depends on Internet of Things (IoT) devices, networked sensors, cloud platforms, and data-driven decision systems. These technologies improve agricultural productivity and monitoring, but they also expand the attack surface of farm cyber-physical systems. This study proposes a benchmark-based explainable machine learning framework for intrusion detection in smart agriculture. The empirical evaluation focuses on the detection and explainability components of the framework, using a consolidated NSL-KDD dataset created by merging CSV-formatted versions corresponding to KDDTrain+.TXT and KDDTest+.TXT and then applying a stratified 80/20 train-test split. After binary target construction, the dataset contains 77,053 normal records and 71,463 attack records. Random Forest and XGBoost models were trained and evaluated for binary intrusion detection. Random Forest achieved an accuracy of 0.9958 and an AUC of 0.9998, while XGBoost achieved an accuracy of 0.9959 and an AUC of 0.9999 under the custom experimental design. SHAP and LIME were used to interpret global feature contributions and local prediction behavior. The strongest signals included traffic-volume variables, service indicators, login-related variables, and host-based traffic statistics. These high values are interpreted cautiously because the study uses a merged and resampled benchmark setting rather than canonical NSL-KDD validation or real agricultural IoT traffic. The generative AI communication component is framed as a future user-centered extension rather than an empirically evaluated contribution. The study contributes a transparent and reproducible benchmark framework that can support future domain-specific validation in smart agriculture cybersecurity.

Keywords

Supporting Institution

This research was supported by the National Center for the Study of Blockchain and FinTech at Morgan State University. Additional support was provided in part by the National Science Foundation under Grant DMS-2235451 and the Simons Foundation under Grant MPS-NITMB-00005320 to the NSF-Simons National Institute for Theory and Mathematics in Biology.

Ethical Statement

This article does not contain any studies with human participants or animals performed by any of the authors. Institutional ethical approval and informed consent were not required as all data utilized in this research consists of simulated, publicly available benchmark network traffic.

Thanks

This work was enriched through the first author's participation in the workshop 'MetaMath: Modeling the Mathematical Sciences Community Using Mathematics, Statistics, and Data Science,' organized by the American Institute of Mathematics and hosted at the California Institute of Technology, December 8-12, 2025. Part of this research was conducted while the first author was a visiting scholar at the Institute for Mathematical and Statistical Innovation (IMSI) at the University of Chicago, which is supported by the National Science Foundation under Grant No. DMS-2425650. The authors also gratefully acknowledge the support of the National Center for the Study of Blockchain and FinTech at Morgan State University. Finally, the authors express their sincere gratitude to the editors and anonymous reviewers of the Journal of AI for their invaluable, professional, and constructive guidance. Their insightful comments and recommendations significantly enhanced the quality of this manuscript. We are deeply appreciative of the time and effort they dedicated to our work.

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Details

Primary Language

English

Subjects

Supervised Learning, Natural Language Processing

Journal Section

Research Article

Authors

Shanzhen Gao
0000-0002-3856-2530
United States

Weizheng Gao ^*
0009-0003-5078-6283
United States

Ephrem Eyob This is me
0000-0003-3590-0028
United States

Ju Hyeong Jin This is me
0000-0002-6653-7383
United States

Publication Date

July 22, 2026

Submission Date

May 13, 2026

Acceptance Date

July 14, 2026

Published in Issue

Year 2026 Number: 10

IZ

https://izlik.org/JA56XH88EZ

Cite

RIS / Bibtex

APA

Gao, S., Gao, W., Eyob, E., & Jin, J. H. (2026). An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer. Journal of AI, 10, 202-216. https://izlik.org/JA56XH88EZ

AMA

1.Gao S, Gao W, Eyob E, Jin JH. An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer. Journal of AI. 2026;(10):202-216. https://izlik.org/JA56XH88EZ

Chicago

Gao, Shanzhen, Weizheng Gao, Ephrem Eyob, and Ju Hyeong Jin. 2026. “An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer”. Journal of AI, nos. 10: 202-16. https://izlik.org/JA56XH88EZ.

EndNote

Gao S, Gao W, Eyob E, Jin JH (July 1, 2026) An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer. Journal of AI 10 202–216.

IEEE

[1]S. Gao, W. Gao, E. Eyob, and J. H. Jin, “An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer”, Journal of AI, no. 10, pp. 202–216, July 2026, [Online]. Available: https://izlik.org/JA56XH88EZ

ISNAD

Gao, Shanzhen - Gao, Weizheng - Eyob, Ephrem - Jin, Ju Hyeong. “An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer”. Journal of AI. 10 (July 1, 2026): 202-216. https://izlik.org/JA56XH88EZ.

JAMA

1.Gao S, Gao W, Eyob E, Jin JH. An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer. Journal of AI. 2026;:202–216.

MLA

Gao, Shanzhen, et al. “An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer”. Journal of AI, no. 10, July 2026, pp. 202-16, https://izlik.org/JA56XH88EZ.

Vancouver

1.Shanzhen Gao, Weizheng Gao, Ephrem Eyob, Ju Hyeong Jin. An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer. Journal of AI [Internet]. 2026 Jul. 1;(10):202-16. Available from: https://izlik.org/JA56XH88EZ

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EA

Esra ALTUNBILEK

Augmented Reality, Intelligent Robotics, Education, Instructional Design, Instructional Technologies, STEM Education, Development of Science, Technology and Engineering Education and Programs

Kevser YILMAZ

Digitalization, Multiple Criteria Decision Making, Logistics, Supply Chains

MB

Mehmet Cem BÖLEN

Information Systems Philosophy, Research Methods and Theory, Management Information Systems, Business Information Systems

MG

M. Önder GÖNCÜOĞLU

Comparative and Transnational Literature, Medieval Literature, Screen and Media Culture, History of Ideas, Ancient Philosophy, Cognitive Anthropology, Anthropology of Media, Evolutionary Psychological Studies, Documentary Film - Political Cinema, Medieval European History, Roman History, Oral History, Literature of History, Christian Studies

Şule ÖZTÜRK BIRIM

Information Systems Development Methodologies and Practice, Decision Support and Group Support Systems, Management Information Systems, Pattern Recognition, Deep Learning, Neural Networks, Machine Learning Algorithms, Data Management and Data Science, Recommender Systems, Natural Language Processing, Business Information Systems

Pijush DUTTA

Deep Learning, Machine Learning (Other), Bioinformatic Methods Development, Biological Network Analysis, Engineering, Optimization in Manufacturing

SS

Sivabalan SETTU

Wireless Communication Systems and Technologies (Incl. Microwave and Millimetrewave)

Dr. Biswadip BASU MALLIK

Data Engineering and Data Science, Data Analysis, Satisfiability and Optimisation, Modelling and Simulation, Artificial Life and Complex Adaptive Systems, Biostatistics, Computational Statistics, Statistical Analysis, Statistical Data Science, Quantitative Decision Methods , Stochastic Analysis and Modelling, Applied Statistics, Experimental Mathematics, Mathematical Optimisation, Numerical Analysis, Finite Element Analysis , Operations Research İn Mathematics, Theoretical and Applied Mechanics in Mathematics, Computational Methods in Fluid Flow, Heat and Mass Transfer (Incl. Computational Fluid Dynamics)

Murat EMEÇ

Information and Computing Sciences, Information Systems, Information Systems Development Methodologies and Practice, Information Systems Organisation and Management, Business Process Management, Decision Support and Group Support Systems, Management Information Systems, Networking and Communications, Cloud Computing, Algorithms and Calculation Theory, Machine Learning, Information Security and Cryptology, Big Data, Data Mining and Knowledge Discovery, Artificial Intelligence, Computer System Software, Computer Software, Social Media Applications and Analysis, Information and Technology Law, Business Analytics, Business Information Systems, Technology Management

Balakrishnama MANOHAR

Deep Learning, Neural Networks, Adversarial Machine Learning

AK

Anita Gautam KHANDIZOD

Pattern Recognition, Deep Learning, Machine Learning (Other), Fuzzy Computation, Natural Language Processing

Hami Onur BINGÖL

Animation, Photography, Fine Arts, Video Art

ES

Esra SÖĞÜT

Cyberphysical Systems and Internet of Things, Deep Learning, Machine Learning (Other), Information Security and Cryptology, System and Network Security, Cybersecurity and Privacy (Other), Data Mining and Knowledge Discovery, Artificial Intelligence (Other)

SC

Subrata CHATTOPADHYAY

Forensic Science and Management, Marketing Management

Alper ŞAKALAR

Interpretation in Western Classical Music, Music Technology and Recording, Interpretation in Turkish Folk Music

EA

Eslam ALJAAFIL

Curriculum Development in Education, Adult Education, Primary Education

Umut Can ÇABUK

Cyberphysical Systems and Internet of Things, Information Security and Cryptology, Cryptography, Wireless Communication Systems and Technologies (Incl. Microwave and Millimetrewave)

Vijaya Kittu MANDA

Metaverse, Natural Language Processing, Planning and Decision Making, Green Economy, Banking Management, Business Administration, Sustainability Accounting and Reporting

	Google Scholar
	ROAD
	Harvard Hollis
	OpenAIRE
	Scilit
	ERIHPLUS
	Web of Science (WoS) Research Commons Database
	Directory of Open Access Journals (DOAJ)

An Explainable Machine Learning Framework for Cybersecurity in Smart Agriculture: Intrusion Detection, XAI, and a Conceptual Generative AI Communication Layer