Cyber security in smart agriculture: Threat types, current status, and future trends

被引:4
作者
Alahe, Mohammad Ashik [1 ]
Wei, Lin [1 ]
Chang, Young [1 ]
Gummi, Sainath Reddy [1 ]
Kemeshi, James [1 ]
Yang, Xufei [1 ]
Won, Kwanghee [2 ]
Sher, Mazhar [1 ]
机构
[1] South Dakota State Univ, Dept Agr & Biosyst Engn, Brookings, SD 57007 USA
[2] South Dakota State Univ, Dept Elect Engn & Comp Sci, Brookings, SD USA
关键词
Smart Agriculture; Cyber Security; Internet of Things (IoT); Precision Agriculture; Agricultural Image Encryption; THINGS; INTERNET; CHALLENGES; PRIVACY; TECHNOLOGIES; SCHEME; CLOUD;
D O I
10.1016/j.compag.2024.109401
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Smart agriculture (SA), which combines the Internet of Things (IoT) with a variety of smart devices including unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and computing systems, is an emerging technology that shows how far the agricultural sector has progressed. Usage of edge computing devices on farms has been growing in the past decades for increasing the yields by improving resource use efficiency through the utilization of temporal, spatial, and individual farm data. With the growing adoption of digital technology, the agricultural sector now offers tools and services for retaining, storing, and analyzing the vast amounts of data produced by Smart Agricultural systems. However, this industry is more vulnerable to cyber security risks due to its growing reliance on technology. This article presents a comprehensive assessment of the state-of-the-art consequences of SA and current cyber security concerns. In addition, this article delves into the structural framework of SA, thoroughly addressing the major security threats at each layer. This study also provides a complete overview of major developments and future research directions in agricultural cyber security for SA. These valuable insights into cyber security will encourage cyber security researchers to suggest more creative and innovative ideas in the future.
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收藏
页数:15
相关论文
共 91 条
  • [1] Cyber-Security Threats and Side-Channel Attacks for Digital Agriculture
    Alahmadi, Adel N.
    Rehman, Saeed Ur
    Alhazmi, Husain S.
    Glynn, David G.
    Shoaib, Hatoon
    Sole, Patrick
    [J]. SENSORS, 2022, 22 (09)
  • [2] A New Image Encryption Algorithm Based on DNA State Machine for UAV Data Encryption
    Alawida, Moatsum
    Teh, Je Sen
    Alshoura, Wafa' Hamdan
    [J]. DRONES, 2023, 7 (01)
  • [3] Cyber Secure Framework for Smart Agriculture: Robust and Tamper-Resistant Authentication Scheme for IoT Devices
    Alyahya, Saleh
    Khan, Waseem Ullah
    Ahmed, Salman
    Marwat, Safdar Nawaz Khan
    Habib, Shabana
    [J]. ELECTRONICS, 2022, 11 (06)
  • [4] [Anonymous], 2014, P AS FED INF TECHN A
  • [5] [Anonymous], 2006, Climate FieldView
  • [6] [Anonymous], 2013, PRESIDENTIAL POLICY
  • [7] [Anonymous], 2022, Agriculture in Bangladesh, P5
  • [8] GPS-Spoofing Attack Detection Technology for UAVs Based on Kullback-Leibler Divergence
    Basan, Elena
    Basan, Alexandr
    Nekrasov, Alexey
    Fidge, Colin
    Sushkin, Nikita
    Peskova, Olga
    [J]. DRONES, 2022, 6 (01)
  • [9] Baum K., 2013, AgriWebb
  • [10] Becker J., 2020, ABC News