IEEE Technology and Society Magazine - December 2020 - 31

is to get participants to reveal critical information about
the security of products they develop or use [12], [13], we
opted to build an in-depth case study, building rapport
with key informants, and using multiple data points
obtained through interviews at different times. We selected participants according to the different roles they play
in the context of precision farming and their ability to
provide further insight into key issues perceived by colleagues in their field (i.e., using them as key informants
to further understand attitudes and requirements from
these types of stakeholders). We interviewed the chief
technology officer (CTO) of a leading commercial vendor
that provides sensor equipment to farms, a farmer using
the vendor's technology able to speak of other colleagues' attitudes and opinions, and a risk analyst from
an international strategy firm tasked with analyzing
cybersecurity of various sectors. We spoke to interviewees multiple times, and performed site visits to a farm
using the vendor's product to gain a better understanding
of the developed technology. Due to the sensitive nature
of discussing security concerns of a commercially available product, we do not disclose the identities of the
interviewees or their organizations. We obtained approval
from our Institutional Review Board (IRB) before any
empirical work began. We did not capture any personal
information from interviews.
Participants were read an informed consent form, and
verbally consented to participating in the study. We used a
common interview guide based (shown in the Appendix)
on questions and items from recent work on secure development [1] and precision agriculture cybersecurity frameworks [8], [34], tailoring the questions to each participant
to account for their different roles and relation to the food
sector and/or the dairy farming technology. Interviews
took place at different sites or via online calls. One
researcher conducted all interviews, sometimes accompanied by a second researcher, which we did in order to
build up rapport and trust given the potentially sensitive
nature of these discussions focusing on security of technology they developed and used. Due to the potentially
sensitive topic of the interviews, we did not record participants, instead taking notes to inform further analysis of
findings. No reimbursement was given to participants.
Using the notes taken during the interviews, two
authors iteratively discussed the findings, developing a
conceptual framework of the key concepts raised by
participants. They did so focused on fostering discussion and building towards a shared understanding of
key points discovered in the interviews, to uncover the
attitudes towards cybersecurity across stakeholders,
guided by Barbour's reflection on qualitative research
noting that " what is ultimately of value is the content of
disagreements and the insights that discussion can provide for refining coding frames " [4].
DECEMBER 2020

∕

The descriptive case study is structured in three
parts, discussing 1) what the technology developed by
the vendor does, 2) what its key requirements are from
the vendor and user perspectives, and 3) how the technology is used and how cybersecurity considerations
from both vendor and user follow from that.

Description of the Technology for SensorDriven Dairy Farming
The vendor is a leading commercial company which provides sensor-driven technologies for precision farming,
used by dairy farms across the world ranging in size
from e.g., 50 to 400 cows. The technological solution,
is, to put it simplified, a sensor-based system for the
monitoring of data relevant to health and welfare of livestock. The operational technology consists of physical
sensors which are worn by individual cows, capturing
e.g., activity data and vital signs. This data is then
relayed towards a central information system where
farmers can monitor all captured data. The software
analyzes this data to provide further decision-making
support on important livestock performance aspects
which may impact the quality of the produced milk, giving indicators for e.g., stress levels, feeding patterns, or
metabolic changes.

Requirements for the Technology-
Data is Everything
If one thing became apparent from our interviews, it is
that data is everything. From the vendor's point of view,

Appendix
Interview guide
■ What are your main priorities during the [development/
use] of this technology? (in order of priority)
■ Do your priorities change when a deadline approaches?
* Why do you feel they [don't] change?
* What about when a competitor seems to [develop/
use] similar technology?
■ What do you feel are the key challenges in [developing/
using] precision agriculture technology?
■ What about security of this technology? Is it something
you worry about?
* Can you think of anything in particular that made you
think so?
* How does security fit into your priorities?
■ To what extent do you [build in/verify] the following
functionality? What do you feel are your main challenges
in doing so? [components necessary for minimal defense
from West (2018)]
* abnormal measurement detection
* access control
* encryption

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