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Security Threats in Agriculture 4.0
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Security Threats in Agriculture 4.0

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (25 October 2022) | Viewed by 16612

Special Issue Editors

Dr. Evgenia Adamopoulou

E-Mail Website
Guest Editor
Institute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece
Interests: communication networks; cognitive networks; network management; energy efficiency; data analytics; Internet of Things; security applications
Prof. Dr. Michal Choras

E-Mail Website
Guest Editor
University of Science and Technology (UTP), 85-796 Bydgoszcz, Poland
Interests: cybersecurity; assurance in EDGE/FOG computing; analytics for critical infrastructure protection and CPS
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

The advent of sensing technologies and their subsequent application to the agricultural domain have impacted this field to such a momentous extent that they have literally triggered a new era, the so-called 4th agricultural revolution or agriculture 4.0. Precision agriculture and smart farming have started to transform agriculture from a labor-intensive to a technology-based domain, promising higher productivity and increased crop yield, as well as more effective livestock raising, through the extensive use of state-of-the art technologies, such as wireless sensing nodes, cloud infrastructure, IoT environments, Unmanned Aerial Vehicles (drones), autonomous tractors, and connected machinery. The application, however, of the aforementioned information and communication (ICT) technologies introduces new vulnerabilities and poses previously unconsidered security threats in this domain, which are often overlooked or being treated out of context, despite the fact that the agriculture and food sector has been recognized as a highly critical infrastructure. Unfortunately, relevant research efforts until today have mostly focused on addressing the conventional vulnerabilities of the involved ICT technologies, such as cyberthreats, as possibly encountered in other industrial contexts, without clear specialization to the risks associated with agriculture. The aim of this Special Issue is to collect research and review papers dealing with the identification of specific security issues and concerns related to the agricultural domain, as well as the presentation and discussion of potential solutions and mitigation measures. Relevant topics include but are not limited to the following:

  • Security of agricultural data;
  • Data management and ownership;
  • Cyberattack risks and prevention actions;
  • Stakeholder awareness of security threats;
  • Security of IoT systems and networks used in agriculture
  • Security of small and large scale monitoring systems used in agriculture
  • Threats for precision agriculture
  • Cybersecurtity of IoT protocols and systems
  • Threats to agri-food-related critical infrastructures (e.g., water management);
  • Security threats across the agricultural supply chain;
  • Misinformation regarding the agri-cultural domain.

Dr. Evgenia Adamopoulou
Prof. Dr. Michal Choras
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • security
  • cyber attack
  • agricultural domain
  • cybersecurity of IoT systems

 

Published Papers (3 papers)

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Research

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19 pages, 8737 KiB  
Article
Secured and Deterministic Closed-Loop IoT System Architecture for Sensor and Actuator Networks
by Hyeon-Su Kim, Yu-Jin Park and Soon-Ju Kang
Sensors 2022, 22(10), 3843; https://doi.org/10.3390/s22103843 - 19 May 2022
Cited by 3 | Viewed by 1876
Abstract
Sensors, actuators, and wireless communication technologies have developed significantly. Consequently, closed-loop systems that can be monitored and controlled by devices in IoT environments, such as farms and factories, have emerged. Such systems are realized by means of cloud-level and edge-level implementations. Among them, [...] Read more.
Sensors, actuators, and wireless communication technologies have developed significantly. Consequently, closed-loop systems that can be monitored and controlled by devices in IoT environments, such as farms and factories, have emerged. Such systems are realized by means of cloud-level and edge-level implementations. Among them, with a model that generates real-time control decisions at the cloud level, it might be difficult to ensure the determinism of real-time control due to communication overheads. In addition, if the actuator is remotely controlled at the cloud level, it is difficult to secure control safety against external hacking or device malfunction. Herein, we propose a system architecture that can fulfil real-time performance and safety requirements with two commonly used devices, Field Edge Unit (FEU) and Current Sensing Tag (CST), in a closed-loop IoT environment. By using these devices, we designed a special architecture that can be commonly used in various closed-loop sensing and actuating applications. In this study, the proposed architecture is evaluated by applying it to a smart farm application. Full article
(This article belongs to the Special Issue Security Threats in Agriculture 4.0)
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17 pages, 12138 KiB  
Article
Performance of Machine Learning-Based Multi-Model Voting Ensemble Methods for Network Threat Detection in Agriculture 4.0
by Nikolaos Peppes, Emmanouil Daskalakis, Theodoros Alexakis, Evgenia Adamopoulou and Konstantinos Demestichas
Sensors 2021, 21(22), 7475; https://doi.org/10.3390/s21227475 - 10 Nov 2021
Cited by 35 | Viewed by 3190
Abstract
The upcoming agricultural revolution, known as Agriculture 4.0, integrates cutting-edge Information and Communication Technologies in existing operations. Various cyber threats related to the aforementioned integration have attracted increasing interest from security researchers. Network traffic analysis and classification based on Machine Learning (ML) methodologies [...] Read more.
The upcoming agricultural revolution, known as Agriculture 4.0, integrates cutting-edge Information and Communication Technologies in existing operations. Various cyber threats related to the aforementioned integration have attracted increasing interest from security researchers. Network traffic analysis and classification based on Machine Learning (ML) methodologies can play a vital role in tackling such threats. Towards this direction, this research work presents and evaluates different ML classifiers for network traffic classification, i.e., K-Nearest Neighbors (KNN), Support Vector Classification (SVC), Decision Tree (DT), Random Forest (RF) and Stochastic Gradient Descent (SGD), as well as a hard voting and a soft voting ensemble model of these classifiers. In the context of this research work, three variations of the NSL-KDD dataset were utilized, i.e., initial dataset, undersampled dataset and oversampled dataset. The performance of the individual ML algorithms was evaluated in all three dataset variations and was compared to the performance of the voting ensemble methods. In most cases, both the hard and the soft voting models were found to perform better in terms of accuracy compared to the individual models. Full article
(This article belongs to the Special Issue Security Threats in Agriculture 4.0)
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Review

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17 pages, 267 KiB  
Review
Survey on Security Threats in Agricultural IoT and Smart Farming
by Konstantinos Demestichas, Nikolaos Peppes and Theodoros Alexakis
Sensors 2020, 20(22), 6458; https://doi.org/10.3390/s20226458 - 12 Nov 2020
Cited by 94 | Viewed by 10203
Abstract
The agriculture sector has held a major role in human societies across the planet throughout history. The rapid evolution in Information and Communication Technologies (ICT) strongly affects the structure and the procedures of modern agriculture. Despite the advantages gained from this evolution, there [...] Read more.
The agriculture sector has held a major role in human societies across the planet throughout history. The rapid evolution in Information and Communication Technologies (ICT) strongly affects the structure and the procedures of modern agriculture. Despite the advantages gained from this evolution, there are several existing as well as emerging security threats that can severely impact the agricultural domain. The present paper provides an overview of the main existing and potential threats for agriculture. Initially, the paper presents an overview of the evolution of ICT solutions and how these may be utilized and affect the agriculture sector. It then conducts an extensive literature review on the use of ICT in agriculture, as well as on the associated emerging threats and vulnerabilities. The authors highlight the main ICT innovations, techniques, benefits, threats and mitigation measures by studying the literature on them and by providing a concise discussion on the possible impacts these could have on the agri-sector. Full article
(This article belongs to the Special Issue Security Threats in Agriculture 4.0)
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