An SDR-Based Cybersecurity Verification Framework for Smart Agricultural Machines

Abstract

The agricultural sector increasingly makes use of automated and/or remotely-controlled machines to improve performance and reduce costs. These machines, called Smart Agricultural Machines (SAMs), integrate different information and communication technologies for monitoring and control purposes and can be remotely controlled by using proprietary protocols. This makes it difficult to assess the vulnerabilities of the system, in particular for non-proprietary-parties. SAMs are cyber-physical systems often employing private protocols and can be objects of attacks. In this context the paper proposes a framework, based on Software Defined Radio (SDR) technology, for cybersecurity verification of SAMs, in order to fill the gap in the state of the art since no technical standard specifically addresses cybersecurity in this environment; the paper describes the testbed developed and exploited to show the effectiveness in detecting vulnerabilities and assessing the SAM security, in particular focusing on the wireless communication channels, and reports the obtained results.INDEX TERMS Smart agriculture, autonomous machines, cybersecurity, software defined radio (SDR), wireless communications, penetration test.

Strategic Analysis for Advancing Smart Agriculture with the Analytic SWOT/PESTLE Framework: A Case for Turkey

“…Recent studies in this field continue to advance our knowledge and understanding of the benefits and challenges associated with SSA [21][22][23]. Ongoing research focuses on innovation in agricultural technology, the impact of smart agriculture on global food security, and the role of policies and regulations in promoting sustainability [24].…”

“…Technological Threats: The Turkish agricultural sector faces technological threats related to cybersecurity risks and dependency on technology and data. Cybersecurity vulnerabilities can compromise the integrity and security of critical digital systems, potentially disrupting agricultural operations [21]. Overreliance on technology and data without sufficient safeguards can lead to data breaches, financial losses, and operational disruptions.…”