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Abstract

Food security is a societal issue of increasing importance requiring careful consideration of the way we produce, process, and distribute food [2], [6]. Digital technologies are increasingly used to optimize processes to support these activities, and therefore, bear important implications for food security. In this article, we focus in particular on technologies used for an important aspect of such security - the effective production of sufficient food, or food availability. Technology has always been an integral part of humanity's efforts to optimize food production processes. Already thousands of years ago, farming tools such as plows were used, first by humans, then with animals, to improve conditions for planting crops and thereby increase yields. Modern food production has seen an explosion of both the amount and the sophistication of technologies used, and has increasingly moved to sophisticated digital technologies such as robots, sensor-driven systems, drones, and automated image analysis [11].
Preprint of: van der Linden, Michalec, and Zamansky, “Cybersecurity for smart farming:
socio-cultural context matters”, IEEE Technology and Society Magazine (forthcoming), 2020
Cybersecurity for smart farming:
socio-cultural context matters
Dirk van der Linden, Ola Aleksandra Michalec and Anna Zamansky
Food security is a societal issue of increasing importance requiring careful consideration of the
way we produce, process, and distribute food [2], [6]. Digital technologies are increasingly used
to optimize processes to support these activities, and therefore, bear important implications for
food security. In this article, we focus in particular on technologies used for an important aspect
of such security—the effective production of sufficient food, or, food availability
. Technology has
always been an integral part of humanity’s efforts to optimize food production processes.
Already thousands of years ago, farming tools such as plows were used, first by humans, then
with animals, to improve conditions for planting crops and thereby increase our yields. Modern
food production has seen an explosion of both the amount and the sophistication of
technologies we use, and has increasingly moved to sophisticated digital technologies such as
robots, sensor-driven systems, drones, and automated image analysis [11].
Such digital technologies, for all the benefits they bring, also come with new challenges,
including that of ensuring their “cyberbiosecurity”—ensuring there are no vulnerabilities at the
intersection of their cybersecurity, cyber-physical security, and their biosecurity [27]. Recent
research has highlighted the variety of cybersecurity threats and attack vectors the food sector
faces (from attacks on farm data or networking and equipment, to the wider supply chain, and
even terrorism, cf. [3], [14]), as well as having documented data breaches in agricultural
organizations, and finding that many farmers and agribusiness owners had been affected by
computer security incidents [16]. While the consequences of attacks on a digitized food sector
may not be as immediately obvious as in other critical infrastructures (e.g., sudden loss of
power, disruption of transport), food availability may likely be impacted as a result of cyber
attacks through a delayed effect. A cyber attack may e.g., cause food production capability to be
lowered and set off a ripple effect moving through the food production chain and related
infrastructures of processing and distribution, until eventually consumers are faced with empty
shelves in their supermarkets [21]. Both the actual technologies used for food production
(operational technology
, or, OT)
and the computer systems that surround it (information
technology,
or, IT), need adequate protection from accidental and malicious attacks that can
disrupt the food production processes. Such attacks have become increasingly common, as
evidenced in increasing numbers of phishing and ransomware attacks on farms and agriculture
companies, such as the ransomware attack on the U.K.’s National Milk Group in 2019 .
1
However, little attention has been paid to the socio-cultural context
in which the digital
technologies for food production is developed and used, and how that may mitigate or worsen
potential attack vectors and the impact of concrete threats.
1 See: https://www.nfuonline.com/sectors/dairy/dairy-news/update-on-the-nmr-ransomware-virus-attack/
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Preprint of: van der Linden, Michalec, and Zamansky, “Cybersecurity for smart farming:
socio-cultural context matters”, IEEE Technology and Society Magazine (forthcoming), 2020
To that end, this article has two purposes: (1) to start a discussion on how the food sector is
stimulated to increasingly adopt new digital technologies, without having as much opportunity to
consider its cybersecurity implications, and (2) to shed light on how socio-cultural context is
intertwined with the development and use of cyber secure technologies, and how unforeseen
risks may arise when technologies developed in one socio-cultural context is adopted in others.
We do so by analyzing the conflicting demands on use of technologies in the food sector in the
U.K. on the one hand, and lack of support for its cybersecurity on the other hand, followed by an
exploratory case study of what drives the development and use of a technological solution for
dairy farming developed in Israel, now increasingly adopted in the U.K.
The digitized food sector: technology first,
cybersecurity later?
The U.K. government, through the Department for Environment, Food and Rural Affairs
(DEFRA), heavily promotes the adoption of operational precision agriculture technologies in
order to stimulate increased efficiency of its food (production) sector [17]. Research has shown
that such technologies exhibits rapid adoption patterns [24], meaning that once some farms
adopt a particular type of technology, it is likely to quickly spread throughout the sector and be
adopted by other farmers. Moreover, the sector typically favors technologies which can be
readily bought and implemented ‘off the shelf’, which has been shown to cause rapid wide-scale
adoption [28]. The food sector is thus pressured to quickly adopt new technologies both
vertically (i.e., the government stimulating adoption of new technology), and laterally (i.e.,
competitors adopting new technology), giving it little time to perform meaningful in-depth
reflections on how these technologies will change the nature of their work and what new risks
and threats it may bring.
In 2017, the U.K. Government explicitly called to defend the food sector from deliberate attacks,
including “cyber enabled industrial espionage, or hacking—gaining unauthorized access to
computer systems, perhaps with malicious intent
” [18]. Yet, even though there is a relevant EU
Directive on security of network and information systems for critical national infrastructure (the
“NIS” Directive), the U.K. Government has not included the food sector to fall within its remit.
While farmers and other stakeholders in the food sector have explicitly called for the NIS
directive to apply to the food sector in order to increase cybersecurity standards, doing so is
postponed until the legislation’s first re-evaluation [19]. Moreover, while relevant Publicly
Available Specifications (PASs) sponsored by the U.K. Government [18] describe several cyber
threats that the food sector needs to deal with (e.g., DDOS attacks on web-based ordering
systems, loss of GPS-based navigation, ex-filtration of sensitive data due to phishing emails),
little guidance is yet given to how to safely and effectively adopt novel technologies while
explicitly understanding what consequences the assumptions of their design entails. There is
thus a clear threat to the food sector from massive disruption as a result of cyber attacks, as
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Preprint of: van der Linden, Michalec, and Zamansky, “Cybersecurity for smart farming:
socio-cultural context matters”, IEEE Technology and Society Magazine (forthcoming), 2020
technologies are increasingly adopted and quickly spread throughout the sector, without
allowing for the time to consider its impact on security (i.e., technology first, cybersecurity later).
Because the U.K. produces almost half of the food it consumes [30] this may be even more
critical, as disruptions in internal food production will make the food sector not resilient to cope
with disruptions from attacks.
Cyber attacks against the food sector may target both the operational technology (i.e., the
actual technologies ‘in the field’), as well as the information technology (i.e., the computer
systems used to control and manage those technologies). Moreover, such technologies adopted
by the U.K. food sector may have been originally developed anywhere in the world. Technology
is not developed in a vacuum, but it is a subject to socio-cultural differences in how we
approach and value both problems and their solutions (cf. [20]). Thus, the way technologies
were developed may have been guided by completely different assumptions and attitudes,
whether stemming from the culture of the society it was developed in, or the culture from the
organization and sector within that society. As a result, technological solutions that make sense
in one socio-cultural context may not make sense in another (cf. [33]). This makes it all the more
critical for a sector where technologies are rapidly adopted and diffused. We, therefore, ought to
understand how the assumptions and expectations from a particular socio-cultural context
where the innovation was originally developed may or may not transfer well to its new location.
However, most of the existing research on cybersecurity in the food sector does not yet address
these assumptions and demands, instead focusing on technical aspects, or proposing
frameworks focused on data analytics and economic incentives. For example, Chi et al.
proposed a framework incorporating the detection of false positives in sensor data,
implementation of access control, and using encryption [8]. Other industrial reports focus
primarily on perceived
risks and threats (e.g., [5]), which has led to researchers offering
quantitative prediction models for vulnerability of technologies in the food sector [34]. Hecht et
al., on the other hand, have offered one of the few in-depth qualitative work identifying a wider
variety of factors contributing to (lack of) resilience in the urban food supply chain [15], noting
the importance of the social environment and organizational culture. The food sector displays
multiple systemic qualities: complexity, interconnectedness, path-dependency, non-linearity; so
goes the argument for the societal challenges surrounding innovation in that sector [32].
Cybersecurity, privacy, transparency of data, sustainability, safety and equitable access—all
these issues depend on each other and ought to be considered in their broader socio-cultural
context to improve resilience of a sector as a whole [26]. This article will demonstrate how
opening up a debate on the socio-cultural dimensions of cybersecurity in food production
innovation will inevitably lead to re-conceptualizing cybersecurity away from purely technical
issues and solutions.
In summary, ignoring the interdependencies between the elements of the food system could
lead to a potential “perfect storm”' of conditions to affect the U.K.'s food availability should
malicious actors be able to successfully disrupt food and agriculture processes by exploiting
vulnerabilities in operational precision agriculture technologies or the information technology
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Preprint of: van der Linden, Michalec, and Zamansky, “Cybersecurity for smart farming:
socio-cultural context matters”, IEEE Technology and Society Magazine (forthcoming), 2020
controlling it—similar to the impact the WannaCry ransomware attack had on the the U.K.’s
National Health Service [9].
Case study—precision dairy farming
With this case study, we aimed to construct a snapshot of the different considerations and
attitudes towards cybersecurity across different stakeholders of the food sector, focusing
specifically on the dairy farming sector in Israel. We focus on this case because the dairy
industry leads the technology in precision livestock farming [25], and Israel is a global leader in
the dairy industry (cf. [29]), which makes it particularly relevant to understand how new
innovative technologies may come about. In our analysis, we compare case study data from
Israel (technology developers and early adopters) with the political and commercial context of
the UK, where the efforts to mobilise early-adoption of precision agriculture are taking place
[10].
We performed a qualitative study using in-depth semi-structured key informant interviews [23]
and site visits, interviewing key stakeholders to build a picture of the cybersecurity situation for
dairy farming in Israel over the span of two weeks. As it is challenging to conduct
interview-driven studies in commercial sectors where the aim 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 type of stakeholders). We
interviewed the chief technoloy officer (CTO) of a leading commercial vendor which 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
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Preprint of: van der Linden, Michalec, and Zamansky, “Cybersecurity for smart farming:
socio-cultural context matters”, IEEE Technology and Society Magazine (forthcoming), 2020
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 did not record
participants, instead taking notes to inform further analysis of findings. No reimbursement was
given for 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]
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 vendo and user follow from that.
Description of the technology for sensor-driven 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, data quality is central in developing an efficient system for dairy farming, as the
data forms the basis to inform any of the farmers’ decision-making. Most development thought
and effort thus goes towards the sensors, assessing what kinds of data can be acquired of the
cow, and how these data can be of value to farmers. Data quality, is thus the name of the game,
and development of the technology focuses on capturing as much meaningful actionable data to
support understanding livestock physiology and behavior.
This aligns well with the priorities of farmers, whose main focus is to use data to understand
their livestock—tracking individual cows to know when to inseminate, generating patterns of
feed intake, understanding behavioral factors affecting their health and welfare. Effectively, the
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Preprint of: van der Linden, Michalec, and Zamansky, “Cybersecurity for smart farming:
socio-cultural context matters”, IEEE Technology and Society Magazine (forthcoming), 2020
farmer noted that they and their colleagues make all decisions based on aggregated data, so
their priority is to get high quality data, and as much of it as possible.
The farmer we interviewed was relatively new to the profession, having been a dairy farmer only
for the past three years. Of those three years, he has always used sensor technologies, never
considering it a challenge to implement and use it, noting that “farmers have always used
technologies to understand their cows for as long as they have existed.”
The farm they work at
has been in business for over 15 years. Different kinds of technologies have come and gone
since then, with farm management adopting new technologies when it allowed them to obtain
more data about their cattle. Their requirements are to obtain more and more data, effectively to
build a detailed model of each individual cow from birth, to analyze how they will behave, and
whether they will become an effective dairy cow. When pressed on what future technologies
could, or should, hold, the answer was similar: more, detailed data, going to the level of
individual genetic information of each cow. They explained this would be great from a business
point of view, as the cost involved in raising a cow to adulthood is significant, and, should they
not be as productive as desired, selling them as meat cows only allowed to recoup some of the
expenses involved in raising them.
Given the focus on data, basic cybersecurity efforts proposed in literature (e.g., [8], [34]) are
important to consider, such as at least ensuring (1) abnormal measurement detection, (2)
access control, and (3) encryption. Detection of abnormal measurements is indeed seen as vital
by the developer given the data-driven nature of the technology and significant development
efforts go towards it. Access control is currently implemented, but limited to sensitive data, such
as current research or commercial data. However, most, if not all data is freely shared owing to
the socio-cultural origin of the agriculture sector in Israel, leading stakeholders to not perceive
significant threats that a malicious actor could carry out with livestock data. Encryption,
however, is not as widely used, likely due to similar attitudes of data being freely shared and
perceptions of that it would be counterproductive to avoid easy access to it.
Using the technology—not all threats are perceived equally by
vendors and users
We further built a more accurate understanding of what threats the food sector in general, and
digitized food production organizations (such as precision livestock farming) in particular, face in
Israel. We interviewed a managing research director of cybersecurity, who focused on modeling
and understanding cyber attacks and risks, including those present in critical infrastructures,
including the food sector.
The primary threat faced by food production companies is similar to that in many other contexts.
There is little evidence of malicious nation state actors or their proxies engaged in cyber attacks,
but there is real-world evidence of attacks conducted by smaller scale cyber criminals motivated
by economic incentives (i.e., theft of data perceived as commercially sensitive, or blackmailing).
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Preprint of: van der Linden, Michalec, and Zamansky, “Cybersecurity for smart farming:
socio-cultural context matters”, IEEE Technology and Society Magazine (forthcoming), 2020
As one could expect from the smaller scale, these do not focus on the operational technologies
used by the food sector, as developing and conducting attacks against new technology requires
an investment of time and effort to understand the hardware, build attacks, and find appropriate
vectors to conduct them. Instead, attackers attempt typical attacks like ransomware and
phishing to affect the information technology layer and blackmail the operators of this IT layer
into making payments to unlock the hardware or avoid release of sensitive data. However, a
more direct threat vector has been used as well, where cyber criminals attempt to compromise
the digital infrastructure of farms through lateral movements, again attacking the information
technology layer primarily (to the point of overruling almost any other attack vector) through
insecure configuration. That is, attackers will attempt to log in to IT systems using standard
credentials, or attempt to abuse management systems such as auto-backup scripts with
embedded credentials. The key threat to technologies in the food sector faced in Israel is thus
towards the information technology (IT) layer
, coming primarily from an economic
perspective.
From interviewing the vendor of the system we studied, these attack vectors seem particularly
salient, as only one real threat was perceived: real-time data loss
, by whatever means. Should
the system crash, whether due to software bugs, environmental factors, or cyber attacks, this
would be a major problem. Given that data is stored on the information technology layer, it thus
seems that the existing attack vectors indeed pose a threat to the cybersecurity of the
technology.
Looking at the farmers using the technology, understanding of what they do to ensure their
cybersecurity, and more importantly, whether they share the same attitude towards data loss
being critical paints a more nuanced picture. In interviews with users of the sensor
technologies, we found that they were not as worried about data loss, whether data itself leaking
by accident or being maliciously extracted. Furthermore, the farmer mentioned that to their
knowledge other colleagues in the field did not worry about this either, even though they
admitted to having a central local server that holds all their real-time and historical data. When
asked why they did not consider data loss to be a threat, they noted two key things:
1. unlike the vendor, they are not worried about loss of real-time data, as this is used for
day-to-day operations rather than long-term analysis and decision making; and
2. they simply do not consider the data as commercially sensitive. In fact, they shared it
freely: “if a veterinarian calls and asks for the data, they get it. If a researcher calls and
asks for the data, they get it.
Farmers did note the impact that a loss of real-time data would have on their ability to
immediately react to their cows, but, besides having never experienced such data loss before,
noted they knew how to run their farm, and that years of experience in day-to-day work meant
that they perceived the impact of not having this data on the productivity and welfare of their
livestock as negligible. On the historical, or aggregated data, they explained that loss of such
data is certainly an issue that has to be dealt with, as this data informs their decision-making.
However, dealing with it was considered trivial because relevant data could simply be obtained
from colleagues, as there is an existing culture of being open and sharing with such data.
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They perceived this attitude towards data sharing to be grounded in the history of the agriculture
sector in Israel, where farming has effectively descended from kibbutzim [singular -kibbutz -]:
ideological collective communities hoping to spread socialism and equality “to all corners of the
land” [22]. These communities were primarily centered around agriculture, and built on an
utopian ideology of social responsibility and sharing of labor [31]. Over time, and in part due to
economic crisis as well as increasing individualism, many agricultural kibbutzim became
privatized, and detached from the original utopian visions, but, nonetheless, had a lasting effect
on the attitude of people working in the sector. Thus, while in modern times the agriculture
sector is no longer exclusively built on collective farming models, the open attitude of the people
involved in the agriculture sector has prevailed. Shared responsibility is effectively seen as
shared benefits, especially when it comes to data analysis. Dairy farms provide data to a central
authority, which allows for more insights than any individual farmer could generate on their own
with their livestock. Almost all dairy farms in the country participate in this, and benefit from the
research and analysis performed centrally to understand their own cows better. As such, they
are happy to share data, and do not consider it a threat if other farmers learn details of their
operations (whether livestock data or even financial data), even meeting up yearly to compare
and learn from each other.
Instead, farmers’ primary concerns in terms of potential cyber attacks were not focused on the
access to data held in their farm’s IT layer per sé, but rather on the accuracy of the data
captured by the operational technology, the actual physical sensors. They noted that it would be
a major problem if sensors were somehow compromised and subsequently provide erroneous
data without them realizing so, as this would lead to making decisions on faulty data, potentially
impacting productivity and welfare of the livestock. However, they perceived this as very
unlikely, assuming it to require physical access, and relevant know-how of the hardware itself.
Indeed, this kind of cyber attack is unlikely given the known threat actors in this context, as
corrupting data would decrease its potential value for anyone involved. Commercial sabotage
could thus be a main driver for such attacks, although in this socio-cultural context such attacks
would not make sense as farmers freely share data and collaborate, rather than compete. Given
the dairy farmers' propensity for sharing files, and learning from each other, this thus seems an
unlikely threat, as it only reduces potential value for any actors involved (less worthwhile data to
learn from, whereas affected target can still learn from untampered data shared by others).
Another critical aspect supporting the cybersecurity of the technology is that farmers in this
culture are open to the vendor gaining access to their information technology in order to
configure the operational technology. That is, they happily grant access to their systems in order
to allow the vendor to set up and configure the technology—reducing the risk of poorly
configured systems that are more susceptible to data breaches.
This combination of the socio-cultural origin of the agriculture sector and its lasting effect on the
attitudes of farmers in terms of data sharing on the one hand, and the primary attack vector
being focused on holding data ransom does not mean that this attack vector as used by cyber
criminals is suddenly gone—they will still attempt to attack IT layers and steal data. But the
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Preprint of: van der Linden, Michalec, and Zamansky, “Cybersecurity for smart farming:
socio-cultural context matters”, IEEE Technology and Society Magazine (forthcoming), 2020
impact
of this primary threat is significantly reduced, as farmers would have no incentive to pay
for e.g., unlocking encrypted data as a result of ransomware attacks, because other farmers
would stand likely in solidarity with them and freely share the data they would need to continue
operations.
Discussion—where it was made matters
Due to its success in increasing dairy farmers’ productivity, the sensor technology has been
increasingly adopted outside of Israel. However, due to the cultural origins of the agriculture
sector and its effect on farmers’ attitudes, key cybersecurity threats faced by the technology are
effectively mitigated (i.e., ransomware threats focused on ‘locking’ away data fail because
day-to-day data is not seen as vital, and long-term data is freely shared across the sector). This
may not be the case in other countries where the agriculture sector may have developed in
different ways, with radically different social origins.
Returning to the U.K. context, in our interview the vendor noted complications with the
technology’s initial adoption in the U.K., as farmers’ attitudes towards data sharing are far less
open. Sensor data is perceived to be more commercially sensitive, as the sector does not
engage in similar open sharing as in Israel, evidenced by the vendor’s experiences, and e.g.,
industrial reports focused on the U.K. context noting the “leaking of confidential farm data”,
including livestock health and economic indicators, as a major threat [3]. This difference in
attitude means that unlike in Israel, farmers may be less likely to allow the vendor access to
their information technology layer to setup and configure the operational technology, increasing
the risk of poor configurations being abused as a threat vector
, and more critically, increase the
impact of such risks
, as farmers in the U.K. more likely cannot fall back on other farmers’
willingness to share data. We thus argue that threats that did not make sense in one
socio-cultural context, also suddenly become relevant again. Compare for example the threat of
commercial sabotage, which was mitigated in Israel due to the sector collaborating
rather than
competing
, now is no longer mitigated, being a more valid threat, and thereby likely also
attracting increased attention from cyber criminals as an opportune attack vector.
Thus, it seems that adoption of technologies built in one socio-cultural context into another
comes with consequences for its cybersecurity, if key assumptions for the safe and secure
operation of the system in-context
are not made explicit. This case study has raised only one
example of such socio-cultural factors, notably, the openness of a sector to share, rather than
compete, and how it changes the impact of cyber attacks. This changes the way that risks
should be analyzed. Typically, risks are assessed by quantifying their impact
(from, say,
negligible to catastrophic)
and their likelihood
of occurring (from, say, rare to certain) (cf. [7]).
For example, if we know cyber criminals are actively using ransomware attacks to lock up IT
layers in the food sector, and
we assume that devices in that layer are poorly protected against
key delivery vectors (e.g., people are not trained to detect phishing, firewalls and antivirus are
not kept up to date), we could say it has a high likelihood. But what would the impact be? If they
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socio-cultural context matters”, IEEE Technology and Society Magazine (forthcoming), 2020
succeed in an attack, and lock up data, farmers would effectively shrug, replace the computer
rather than pay the ransom, and go about their day, using data willingly shared by other
farmers. More realistically, the likelihood of the attack is affected by the socio-cultural context of
the technology as well, as farmers are happy to allow the vendor to securely configure the
technology, thereby reducing the likelihood of a poor configuration being abused as a threat
vector.
The socio-cultural context
in which technology is situated thus has an effect on the impact of a
cyber attack. But the very likelihood of it from the attackers’ point of view may also be affected,
as cyber criminals will (eventually) realize their actions are fruitless in this context, making them
drop such attack vectors for better opportunities. Thus, in order to assess the socio-culturally
dependent risk of a cyber attack, both impact and likelihood need to be understood in context of
the sector and the attitude of people within it. This raises an important call for research in
protection of national infrastructures, or indeed, any sector to better understand digital
technologies and their cybersecurity in the socio-cultural context they are situated: what
socio-cultural factors of technology development and use may alter, for better or worse, the
impact and likelihood of cyber attacks?
Acknowledgments.
This research was supported by a grant from the Ministry of Science & Technology, Israel
(MOST), and by the Cabot Institute Innovation Fund. The Cabot Institute for the Environment is
a diverse community of 600 experts, united by a common cause: protecting our environment
and identifying ways of living better with our changing planet. Together, we deliver the evidence
base and solutions to tackle the challenges of food security, water, low carbon energy, city
futures, environmental change and natural hazards and disasters.
Author biographies
Dirk van der Linden
is Lecturer (Assistant Professor) at Northumbria University, U.K. His
research interests include software engineering, cyberpsychology, and technology for animals.
Contact him at: dirk.vanderlinden@northumbria.ac.uk.
Ola Aleksandra Michalec
is Research Associate at University of Bristol, U.K. Her research
interests include policy and politics, science and technology studies, and partnership building.
Contact her at: ola.michalec@bristol.ac.uk.
Anna Zamansky
is Associate Professor at University of Haifa, Israel. Her research interests
include information systems and technology for animals. Contact her at:
annazam@is.haifa.ac.il.
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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?
abnormal measurement detection
access control
encryption
Page 13 of 13
... The interconnectivity of these technologies within a single farm or production facility and in exchange of data with suppliers and vendors creates unsupervised networks of information. With the adoption of these technologies comes increased risks for cybersecurity attacks on farms and agribusinesses (van der Linden et al., 2020). These attacks have the potential to disrupt food supply chains, damaging the bioeconomy and communities. ...
... Protecting agriculture and the food supply chain is a high priority, especially with increasing risk of food insecurity brought on by the Covid-19 pandemic (Laborde et al., 2020) as well as the rapid expansion in the global population. Unfortunately, it is uncommon for farms to have response plans for cyber penetrations (van der Linden et al., 2020) or to recognize the risks associated with corrupted data on decision making. Perceived risk of penetration and perceived benefits from better security are two influential factors for adopting better security habits (Geil et al., 2018). ...
... Current literature in cyberbiosecurity points out that agriculture is becoming more and more reliant on the capabilities of technology, thus bringing along cybersecurity risks (van der Linden et al., 2020). Also, more resources need to be invested into cyberbiosecurity research and development to prevent large-scale issues from arising (Mueller, 2020). ...
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Agriculture has adopted the use of smart technology to help meet growing food demands. This increased automation and associated connectivity increases the risk of farms being targeted by cyber-attacks. Increasing frequency of cybersecurity breaches in many industries illustrates the need for securing our food supply chain. The uniqueness of biological data, the complexity of integration across the food and agricultural system, and the importance of this system to the U.S. bioeconomy and public welfare suggests an urgency as well as unique challenges that are not common across all industries. To identify and address the gaps in awareness and knowledge as well as encourage collaborations, Virginia Tech hosted a virtual workshop consisting of professionals from agriculture, cybersecurity, government, and academia. During the workshop, thought leaders and influencers discussed 1) common food and agricultural system challenges, scenarios, outcomes and risks to various sectors of the system; 2) cyberbiosecurity strategies for the system, gaps in workforce and training, and research and policy needs. The meeting sessions were transcribed and analyzed using qualitative methodology. The most common themes that emerged were challenges, solutions, viewpoints, common vocabulary. From the results of the analysis, it is evident that none of the participating groups had available cybersecurity training and resources. Participants were uncertain about future pathways for training, implementation, and outreach related to cyberbiosecurity. Recommendations include creating training and education, continued interdisciplinary collaboration, and recruiting government involvement to speed up better security practices related to cyberbiosecurity.
... In practice, ICS consists of several types of control systems, including supervisory control and data acquisition (SCADA) systems and hence the two categories (ICS and SCADA) were combined. Operational systems seem to be more susceptible to cyber-attack if they are standardized, since security deficiencies may be duplicated across the entire network , and if technologies for data collection (such as IoT (van der Linden et al., 2020;Sontowski et al., 2020;Bayramova et al., 2021)) and data recovery, (such as data server (Vinatzer et al., 2019;Bayramova et al., 2021)) are involved. IT and communication infrastructure systems and, payment systems (such as debit and credit card systems, or bitcoin), were widely targeted by cyber-events, both within the F&B industry and outside it. ...
... However, only one manuscript was published in each of the years 2012 (Rohn and Erez, 2012), 2016 , 2017 (van der Linden et al., 2020) and 2018 (West, 2018). The research productivity on this topic than quadrupled in the years 2019 (Vinatzer et al., 2019;Duncan et al., 2019;Beluli, 2019;Mondal et al., 2019), 2020 (Etemadi, 2020;Chun Hsion et al., 2020;van der Linden et al., 2020;Sontowski et al., 2020), and 2021 (Fernandez et al., 2021;Tatar et al., 2021;Drape et al., 2021;Jarjoui et al., 2021;Bayramova et al., 2021), maintaining a constant trend over this three-year period. It can be seen from Fig. 3, that several themes emerged overtime: the definition of agroterrorism, the study of the entire FSC, IT and communication infrastructure as industrial assets involved in cybersecurity issues, and, the study of the related risks. ...
... van der Linden et al., 2020;Vinatzer et al., 2019;Sontowski et al., 2020;Bayramova ...
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Given the tendency of food companies to adopt digital technologies throughout the food supply chain and the importance assumed by the security and reliability of these systems in Industry 4.0 applications, we carried out a systematic literature review of cybersecurity issues in food and beverage industry. The research methodology was defined based on the PRISMA guidelines, and a reference framework was created that leveraged a thematic analysis of the following content categories: definitions, focus on the food and beverage industry, characterization of cybersecurity, and management of cybersecurity risks. This analysis allowed us to compare the advancement in cybersecurity in the food and beverage industry with those proposed in the literature for the Industry 4.0 paradigm. This comparison is useful, since although the Industry 4.0 paradigm finds a wide range of applications in such domain (e.g., Agriculture 4.0), the structural characteristics of this sector, its supply chain and products create a specific context and situations that may require ad hoc cybersecurity strategies and solutions. The body of knowledge on the food and beverage industry resulted mature in terms of definitions, the target supply chain, industrial assets, and cyber-threats, but requires future research effort in terms of practical analysis that can fill the emerging gaps in relation to risks, countermeasures, vulnerabilities, solutions and guidelines. The results of our review guided discussions, implications and definition of future research routes.
... Chi et al. [61] envisions that a security framework for PA would comprise of three components: 1) abnormal measurement detection, 2) access control, and 3) data encryption. On the other hand, Linden, Michalec, and Zamansky [62] argue that there is a socio-economic aspect of such cybersecurity concerns in PA. The interviewed dairy farmers in this study mention that although data loss will not stop them from doing their jobs but in the long run data loss is detrimental to their informed decision-making process. ...
... Though security attacks can target confidentiality and availability as well [57], [63], we believe threats to the integrity of data will create the greatest havoc. This is consistent with the farmers' experiences listed in [62]. In precision agriculture, decisions and actions are based on processing sensor observations (e.g., image data) to form state estimates (e.g., environmental maps). ...
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Precision agriculture is the collection of hardware and software technologies that allow a farmer to make informed, differentiated decisions regarding agricultural operations such as planting, fertilizing, pest control, and harvesting. In recent years, advances in agricultural machinery and the emergence of agricultural robots continuously increased the resolution at which differentiated treatment is possible. This creates a corresponding need for information at a fine spatial and temporal resolution. Autonomous multi-robot systems (e.g., unmanned ground and aerial vehicles) are some of the most promising approaches for such information collection in open-air farms. In this paper, we survey the current state and challenges of multi-robot information gathering for precision agriculture, with a special focus on maximizing information and ensuring the security of the collected data while simultaneously keeping energy consumption in check.
... research investigating the use of animal-centered technology has hinted at [102,103,122]. Dog activity trackers may indirectly capture unrelated bystanders' behavior, impacting on privacy, while industrial technology for farm animals may unintentionally reveal commercially sensitive information, and poorly designed wildlife technology may affect more ecosystems than envisioned and intended. ...
... Understanding what else the animal data captured within an IIS may reveal, whether directly, or by processing it further, is vital to understand both the potential added value of such data, and how sensitive it may be-and thus, to what extent security and privacy considerations need to be given serious attention while designing the IIS. Data captured by smart farming solutions, for example, might be commercially sensitive and pose a threat to the viability of an agribusiness if it were to leak [33], although such considerations are also dependent on the socio-cultural makeup of the sector and to what extent data is freely shared among colleagues and competitors [103]. Perhaps more pressing as a challenge to the design and use of an IIS are the unexpected things that may be inferred from data. ...
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Full-text available
This article introduces a new class of socio-technical systems, interspecies information systems (IIS) by describing several examples of these systems emerging through the use of commercially available data-driven animal-centered technology. When animal-centered technology, such as pet wearables, cow health monitoring, or even wildlife drones captures animal data and inform humans of actions to take towards animals, interspecies information systems emerge. I discuss the importance of understanding them as information systems rather than isolated technology or technology-mediated interactions, and propose a conceptual model capturing the key components and information flow of a general interspecies information system. I conclude by proposing multiple practical challenges that are faced in the successful design, engineering and use of any IIS where animal data informs human actions.
... The attackers usually display a ransom demand on the computer screen to release the locked information. Phishing is also a common cybersecurity scam that can harm farms' digital infrastructure (De Araujo Zanella et al., 2020;Van Der Linden et al., 2020). Through phishing, a hacker obtains some sensitive information through an email, phone call, or text message. ...
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Full-text available
The growth in the use of Information and Communications Technology (ICT) and Artificial intelligence (AI) has improved the productivity and efficiency of modern agriculture, which is commonly referred to as precision farming. Precision farming solutions are dependent on collecting a large amount of data from farms. Despite the many advantages of precision farming, security threats are a major challenge that is continuously on the rise and can harm various stakeholders in the agricultural system. These security issues may result in security breaches that could lead to unauthorized access to farmers' confidential data, identity theft, reputation loss, financial loss, or disruption to the food supply chain. Security breaches can occur because of an intentional or unintentional actions or incidents. Research suggests that humans play a key role in causing security breaches due to errors or system vulnerabilities. Farming is no different from other sectors. There is a growing need to protect data and IT assets on farms by raising awareness, promoting security best practices and standards, and embedding security practices into the systems. This paper provides recommendations for farmers on how they can mitigate potential security threats in precision farming. These recommendations are categorized into human-centric solutions, technology-based solutions, and physical aspect solutions. The paper also provides recommendations for Agriculture Technology Providers (ATPs) on best practices that can mitigate security risks.
... We assumed that the security of agricultural systems based on IoT can be accomplished by current technologies of authentication, access control, and confidentiality of the stakeholders. Nevertheless, the security obligations and other sub-systems in precision agriculture, e.g., faultdiagnosis as well as reaction systems toward risks and cyberattacks [53], will be considered in future works. ...
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... Consider another example. An AgriTech company develops a piece of sensor-driven hardware that works perfectly in the context of their professional culture, and, through a careful balance of human behaviors and expectancies of the sector in that country, come together to mitigate, indeed nearly nullify, the impact of the most prevalent cyber threats [8]. That mitigation is not borne out of the technology itself, but relies on the complex, situated nature in which it exists. ...
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