Preliminary Examination of Emergent Threat and Risk Landscapes in Intelligent Harvesting Robots
Source abstract
Abstract
Recently, many farmers have started using robots to help with labour-intensive harvesting operations and deal with labour shortage that was also a negative consequence of the recent COVID-19 pandemic. Intelligent harvesting robots make farming more efficient and productive. However, and like any other technology, intelligent harvesting robots come with a security risk, as threats can damage the robotic system and wreak havoc before the farmer/operator realizes it. This paper focuses on analysing the threats against the security of harvesting robots alongside with the safety implications that may rise if the robotic system is compromised. We analysed an actual asparagus harvesting robot and looked at others in the literature. We identified several security threats which we classified into five categories: network, hardware, software, Artificial Intelligence (AI) and cloud security issues. We selected three interesting attack scenarios for a deeper analysis. Our results suggest that these robots have a large attack surface that can lead to exploits with immense financial and operational impacts.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Smart Agriculture and AI
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
WMG, University of Warwick, Coventry CV4 7AL, UK
Muddy Machines Ltd., London SW6 4SL, UK
Funding
UK Research and Innovation (UKRI)
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