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Hadtudományi Szemle
Kristóf Kralovánszky�
Certain Connections between
Cyber Operations, Artificial Intelligence
and Operational Domains
Abstract
The relationship of operational domains with various systems based on artificial
intelligence is becoming more profound and more diverse. The ability to influence
decision-making mechanisms can pose serious risks that need to be identified and
interpreted. Cyberspace is the carrier of artificial intelligence, but the latter as an ope-
rational domain has not yet been identified. The goal of this study is to examine certain
relationships between cyberspace, artificial intelligence, and operational domains from
a state-will enforcement perspective, using mostly qualitative tools, combined with
quantitative elements. As a result, this paper finds the need to review defence doctrines
from a cyber operational perspective and suggests addressing artificial intelligence in
a much broader context, especially in the defence and military contexts.
Keywords: cyberspace, military domains, artificial intelligence, critical infrastructures
1. Introduction
Discussing technical subjects from a military science (not engineering) perspective might
seem like a contradiction in terms. To a specific aspect, it is, but above a particular level,
the two separate threads (science and engineering) must come together and strengthen
each other. Taking cyber operations and cyberspace as an example, such consolidations
evolve to become policy. In many cases, strategy can remain below the radar, mostly
for operational safety reasons – which is the case in most cyber operations.
According to Clausewitz, war itself is an instrument for political act. If we generalise
this principle, we can safely say that military operations are the same instruments, but
University of Public Service, Doctoral School of Military Engineering, PhD student; University of Public Service,
Department of Electronic Warfare, junior Assistant Professor; e-mail: kralovanszky.kristof@uni-nke.hu
Such strategies do exist but are h ighly classified, so the result is that they are not visible for the public eye.
Carl von Clausewitz, A háborúról (Budapest: Zrínyi Kiadó, 2014).
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Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
possibly on a lower level. However, if we look back to the 19th century, there were only
two domains that an armed force could use: land and sea. In that sense, Clausewitz’s
thinking was limited to those two areas.
The 20th century brought a new domain: the air force. The 21st century (and only
21 years have passed from it) already brought two new domains: cyber and space.
The force behind a political act remains unchanged: states wishing to pursue and
enforce their interests to achieve the best possible position within a region or in the
system of certain states.
2. Enforcement of State-will
It is essential to distinguish between political- and state-will enforcement. There is
always a political will behind the enforcement of a state’s will, but this special enforce-
ment is typically only possible by a political force with state authorities and power. It is
possible that in domestic politics, a given party or organisation has a serious political
weight (in fact, it may even be in the majority), but it is still incapable of enforcing
its will at the state level. This study further interprets political will as the motivation
behind state-will enforcement.
In most cases, enforcing one’s will seeks to make optimal use of its resources,
but at the same time, politics very often mixes emotions into its actions. This is part
of the reason why many state-run operations are not (always) rational.
In each case, a state seeks to assert its own will and achieve its own goals – but
it does so in a dynamically changing international environment in which power rela-
tions are also constantly changing. As a result, it will at all times strive to achieve
the best position in a given situation and, in many cases, afford a partial violation of
the sovereignty of other states, since sovereignty is not an absolute concept and its
interpretation follows changes in the political environment in the same way.
This logic is perfectly valid for cyber operations as well, as state (subsidised)
enforcement is precisely the same will. As with all military operations, all state ope-
rations will evaluate targets and designate assets once targets have been identified.
Even in this process, there can be a kind of goal, since the use of a particular tool can
be of message value in itself.
The growth of cyber operations is primarily due to their efficiency and excellent
price/value ratio. However, they would be almost entirely worthless by themselves, as
it is impossible to occupy physical space with cyber operations. Therefore, a suitable
Space could be considered an older domain in a military context as well, consid ering that President Ronald Reagan
announced the Strategic Defense Initiative in 1983. This program was meant to be of defensive nature only and
considered attacks initiated from the air, land or sea and not from space. From a definition perspective, a domain can
be used to initiate, perform and conclude an armed conflict in that same domain.
Emotions and rational decisions usually do not mix. In an id eal scenario, a state action’s outcome is carefully calculated,
however, strong emotions can easily override such calculations. The strength of emotions and the level of override
can be in direct proportion.
Gergely Varga, ‘A vesztfáliai szuverenitás érvényessége a nemzetközi kapcsolatokban’, Nemzet és Biztonság 8, no 1 (2015),
30–38.
A kinetic detonation, as a response, can be carried out in several ways: with a missile, an explosive deployed on the
ground, a suicide bomber. The method can also be interpreted as a reference to the de fendant.
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Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
target is also needed for cyber operations to work. Humankind has created more and
more vulnerabilities in its own environment, and one of the best examples of this is
the system of critical infrastructures.
In offensive cyber operations, the use of conventional armed force has become
partly redundant, as the operation itself requires intelligence (i.e. information related
to the systems to be attacked) and an appropriate IT system/knowledge. This may
very well be available to the armed forces, but any state-aided organisation may also
be able to carry out the operation, as it does not require a weapon in the classical
sense and the logistical background that serves it.
The smooth operation of critical infrastructures, including the continuous and stable
operation of their interdependencies, is a precondition for the stability of a country.
Thus, failures of some critical components (whether in the same or a different sector)
for weeks or more will alone result in almost guaranteed instability, both in economic
and domestic terms. This is mainly why the target value of critical infrastructures is
exceptionally high from an attacker’s perspective.
On the defence side, the armed forces of a given country are, in typical cases,
unavoidable. In the case of a cyberattack, especially when targeting a critical infra-
structure, the attacker’s intention to do damage is clear and it is equally clear that
they wanted to harm the attacked country as a whole. Therefore, from this point of
view, it is not necessarily relevant whether kinetic destruction has occurred or whether
anyone has lost their life. A threshold needs to be set beyond which an offensive cyber
operation should be interpreted as an armed attack. However, pre-determining this
threshold can be a serious problem, as it is difficult to generalise the damage caused
by an unforeseen attack vector. It is also not practical to start with an itemised list
of infrastructures and damages since it would give unnecessary ideas to a potential
attacker. Determining the threshold is, therefore, a sensitive political issue for these
reasons, as well.
Therefore, it can be concluded that state-will enforcement through cyber ope-
rations raises several critical questions related to defence doctrines that should be
addressed quickly and effectively.
3. Artificial intelligence as a defining new area
It is important to discuss an exceptionally rapidly evolving area, which is increasingly
becoming a determinant of our standard technologies: artificial intelligence (AI).
There have always been resources in societies whose targeted attacks could have caused severe damage. Such were
wells (thousands of years ago), which were often poisoned by adversaries, thus severely limiting the access to potable
water for those living there. It is equally true today that the infrastructures requiring the highest level of protection
are drinking water reservoirs and drinking water distribution systems.
This summary might be an oversimplification, but in its true essence, it reflects reality. Obviously, the armed forces’
own intelligence background (also) may already be a condition for obtaining credible and actionable intelligence.
Jori Pascal Kalkman and Lotte Wieskamp, ‘Cyber Intelligence Networks: A Typology’, The International Journal of
Intelligence, Security, and Public Affairs 21, no 1 (2019), 4–24.
László Kovács, A kibertér védelme (Budapest: Dialóg Campus Kiadó, 2018).
Peter Layton, ‘Fighting Artificial Intelligence Battles. Operational Concepts for Future AI-Enabled Wars’, Centre for
Defence Research, Australian Defence College, Joint St udies Paper Series, No. 4.
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Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
It will be confirmed or refuted in the coming years, but AI is increasingly beginning
to have domain-like characteristics. However, to better understand this, we need to
look back at earlier stages of electronic warfare. Even before cyberspace and cyber
operations, there were computers, there were computer networks that our society
actively used. They were parts of everyday life – especially in the economic and military
spheres. As time went by, their importance grew, their field of application widened,
and they started to play a decisive role in the functioning of society.
Regarding their components, we are talking about electronic devices that existed
before, but their development has significantly increased their processing speed and
wide availability. Examining the development of similar properties of AI, we find
precisely the same thing. AI is based on computer systems, just as computer systems
were based on electronic devices. Self-propelled (sub) AI systems are now part of
every new smartphone on the market. Almost all new (up-to-date) desktop operating
systems already have machine learning systems. Such are the built-in firewalls and
intrusion protection systems. Based on our web browsing, various AI systems deliver
customised advertisements to us. Our electronic mail systems also perform SPAM
filtering using AI-based algorithms.
However, one of the most significant differences is that with proper hardware, it
is only a matter of software if AI is present or not. In other words, if the appropriate
hardware is available, an AI system can be installed on the hardware without needing
to replace additional hardware. The direct consequence of this is that an AI system can
be upgraded through software only, which provides additional capabilities or greater
efficiency. To achieve the same in the past, parts had to be replaced in an electronic
system or a new machine had to be purchased.
Behind the modern analytic tasks, we will find AI-supported systems in almost
all cases. The kind of spread that was visible between the birth of electronic devices
and cyberspace can be observed between cyberspace and AI systems. However, there
is another significant parallel. Cyberspace cannot be interpreted and is dysfunctional
without infocommunication systems. The same is true for AI systems: they are in ope-
rable without infocommunication foundations. But there is a crucial difference. By
definition, a computer alone (without network connections) is not part of cyberspace.
An AI system (when properly configured) can work on its own. This, of course, requires
that the AI system be loaded with the right amount and quality of data and have
a local user interface. If these are available, the AI system can answer the question
(posted) defined in the user interface. At the same time, isolation also means that
the decision-making process will be based only on the stored data – although under
certain circumstances, this decision-making database can be updated manually (e.g.
via USB drive).
In a holistic view, cyberspace is a vital element of all military domains, AI is
rapidly starting to behave very similarly.
Négyesi Imre, ‘A mesterséges intelligencia katonai felhasználásának társadalmi kérdései’, Honvédségi Szemle 149,
no 1 (2021), 133–144.
Jared Donnelly and Jon Farley, Defining the ‘Domain’ in Multi-Domain (Joint Air Power Competence Centre, 2019).
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Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
4. Possible risks of AI systems
Based on the above, the operation of AI systems should be divided into two parts:
distinguished between networked and non-networked AI systems. One crucial
question is whether a non-networked AI system could pose a risk to the operator
(organisation) or to the country of operation? The answer is a resounding yes, as it
may be able to make autonomous decisions independently of the network. From
a different perspective, the risk lies not only in network availability but also in deci-
sion-making and its use.
Going further on this idea, it is necessary to examine how the risks of decision-making
can develop? AI systems, like all infocommunication systems, consist of at least one
hardware and one software component. The operation of the software part is based
on the standard operation of the hardware elements. However, an individually modi-
fied, unique hardware device can implement the standard operation and, at the same
time, additional functionality according to the will of the modifier. So it is possible to
create hardware that matches the traditional version in all respects (in appearance,
design and basic operation) and has additional capabilities. A simple example of this
is a phone charging cable that incorporates a miniature web server and data logger.
It looks virtually indistinguishable from a traditional, factory-charged charging cable,
but it gives its installer (partially) free access to the phone they charge, so an attacker
can easily learn about the data stored on the device.
A software-based attack on an AI system can also work without a network con-
nection. During the development of the AI system, backdoors can be created, which
are known only to the developer and remain hidden from the user (operator). Through
such a backdoor, not only data can be extracted from the system, but new data can
be recorded or the decision-making process can be modified. During the learning
process, intentional mistakes are possible where a recognised object is associated with
the name of another object, i.e. an “apple” will be treated as a “lemon” or a “chair”.
The risks involved are almost self-evident.
A similar problem is when an AI system judges incorrect behaviours to be correct
and vice versa. A good example of this problem was in 2016, when an AI-based chat-
bot developed by Microsoft called Tay, was launched as a sociological experiment by
its creators (otherwise intended for entertainment). The app should have picked up
the style of a 19-year-old, but as part of that, he very soon began sending extremely
racist and inciting messages. Those who communicated with Tay soon realised how it
was possible (and how easy it was) to teach him, and the bot was directed to Internet
content from which he gained this blatantly extreme knowledge. Following serious
community outrage, the manufacturer shut down Tay less than 24 hours after the
The vast majority will be networked AI systems.
See https://shop.hak5.org/products/o-mg-cable-usb-a
The course of attack is much more complex, but the concept works in the real world with proven records.
Paul Maxwell, Artificial Intelligence Is the Future of Warfare (Just Not in the Way You Think) (Modern War Institute,
2020).
Rachel Metz, ‘Microsoft’s Neo-Nazi Sexbot Was a Great Lesson for Makers of AI Assistants’, MIT Technology Review,
27 March 2018.
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Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
start. Such flaws were more common 3–4 years ago, but manufacturers were quick
to respond, and similar fundamental problems became rare. It can also be considered
a development curve which is now in the past. However, technology evolved to the
next level, and flaws of similar sizes are a lot more challenging to pinpoint.
5. AI systems built on each other
Likewise, the risk of manipulating a voice recognition and dictation system can be
extremely high. The software itself recognises the voice of the given (logged in) user
and describes it in the text field of an application. If the application is not operated
by the initial user, the recognition will start to be distorted and after a few hours the
voice recognition of the original user will start to fail. In a critical case, the adaptation
of the original user may be so distorted that it becomes necessary to delete it. The
audio adaptation file of the same system, which contains the recognition dictionary,
can be attacked, for example, the word “left” can be changed to “right”, which can
be a severe problem in a medical application. In this case, the system recognises the
word “left” and then describes it as “right” according to the dictionary.
The former example is very thought-provoking given that the number of (mobile)
devices running an application with voice recognition functionality is expected to be
around 7– 8 billion by the end of 2021, meaning that on average, such a device will reach
every inhabitant of the Earth. An additional risk is that apart from similar applications
available only in the Chinese domestic market, this value is shared by five manufacturers:
Apple Siri, Google Assistant, Microsoft Cortana, Amazon Alexa, Samsung Bixby.
One of the most spectacular appearance and (accessible to anyone with inter-
net connection) is the appearance of “deepfake” technology. It is able to montage
a user-narrated text from a few photographs of an existing person to that person,
resulting in any text that can be told by a freely chosen person. There is an amateur
version of this software that can be downloaded to a smartphone, with limited char-
acters and basic videos, so its fake is relatively noticeable. A professional solution
to this can also be found as early as 2017, from scientific research and development
at Washington State University. The authenticity of videos of this quality can often
only be established by secondary means or indirectly – using highly sophisticated
analytic and forensic technology.
AI systems as mentioned earlier can be extremely complex, which also means that
they involve interdependent decision-making. That is, they have separate AI subsystems
operating on several levels, where the output of one AI subsystem becomes the input
of the subsequent system. If there is no comprehensive control (in the received data/
Paul Mason, ‘The Racist Hijacking of Microsoft’s Chatbot Shows How the Internet Teems with Hate’, The Guardian,
29 March 2016.
Sandra Vogel, ‘More Digital Assistants than People by 2021 Says Ovum’, Internet of Business, 15 July 2021.
Using only a few photos will not result in totally lifelike appearance, however, the teaching of hundreds of images
from different angles will considerably improve the quality of the forged footage.
Jon Porter, ‘Another convincing deepfake app goes viral prompting immediate privacy backlash’, The Verge, 02 Sep-
tember 2019.
Jennifer Langston, ‘Lip-Syncing Obama: New Tools Turn Audio Clips into Realistic Video’, UW News, 11 July 20 17.
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Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
information) between the interconnected systems, an additional risk (and possibility
of attack) appears. This is because it becomes unnecessary for the attacker to get to
know and manipulate the AI algorithm in detail. It is sufficient to attack transitions
between subsystems and inject a data set desired by the attacker as the data input
of a higher system. If this is accepted as authentic by the higher system, the attack
is successful and the attacker achieved the goal of influencing.
In the case of newer surveillance cameras (used both for civilian and military
purposes), the primary processing of AI takes place in the camera, which a few years
ago was only possible on the server side due to the high CPU performance demand.
This technological step also allows for the mass spread of facial and behavioural
recognition technologies (systems). However, examining the risk side, autonomous
decision-making at the law enforcement level appears, a closer observation of a per-
son can begin – based on an AI system’s evaluation. Ideally, this poses no risk to the
observed individual since recordings of him or her will be deleted after a specified (and
relatively short) period of time. The problem is much more serious when statistics
records the fact of observation without stating that such observation was unjustified
and was without true cause. It may be that a person actually needs to be monitored
once, but system statistics will show that they have already been monitored four
times – but each time this was due to an error in the AI’s decision.
Facial recognition and, more broadly, biometric identification are increasingly
popular and relatively widely accepted authentication methods. It has now been
proven that their reliability is far from being as high as manufacturers or implement-
ers want it to be. It is also true that the biometric part itself – that is, the iris, the 3D
portrait, the vein, etc. – is difficult to falsify, but the procedure has an intermediate
step: where the read data is compared with the data stored in the databases. This is
because the originally uploaded face image can be modified by uploading a properly
prepared duplicate so that it can be identified as another person during the com parison.
The novelty of this type of attack is that it is not necessary to know the internal AI
algorithms of the facial recognition system for this deception.
Basic AI implementations can be found in numerous military applications, similar
to civilian use: semi-autonomous vehicles, robots and biometric recognition. One
precious and specific military use is in multisource intelligence evaluation, especially
in a combat/tactical environment. Deep descriptions of such systems in unclassified
documents are scarce. These are good warnings that widespread new technology
in crucial systems can be problematic without proper (real world) experience. The
use of such technologies in crucial systems without extensive field testing can be
dangerous. Finding the right balance between test-times and speedy implementation
can be a true challenge.
Kristóf Kralovánszky, ‘A kibertér fejlődése’, Hadmérnök 14, no 4 (2019), 197–212.
See https://adversa.ai/report-secure-and-trusted-ai/
Adriana Gibson, Andrew J Merchant and Brandon D Vigneron, ‘Autonomous Systems in the Combat Environment:
The Key or the Curse to the U.S.’, The Strategy Bridge, 08 October 2020.
Especially in military identification/authentication processes.
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Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
6. Autonomous decision-making
A much more serious dilemma is when the use of lethal force (as a design goal) becomes
possible based on the decision of AI systems. In March 2020, a Turkish STM Kargu-2 4-rotor
drone caused the death of an individual in Libya. This drone is programmed to be
able to identify targets even in the event of loss of communication with the controller
and destroy such target after positive identification. That is, there does not necessarily
have to be operator approval between the identification and the destruction stages.
This particular type of drone destroys the target in such a way that an explosive device is
mounted on it, and the aerial vehicle guides itself to the target at maximum speed. This,
of course, destroys the drone itself as well, but even so, the aircraft part is extremely
cheap, as it is worth only a few thousand Euros (excluding the warhead). And once
destroyed, the same controller will control the next, new drone.
The above technology can, of course, be extrapolated since it does not matter
to the software whether it guides a drone onto the target, or it does the same with
a rocket with greater destructive power in the classical sense. The more important
question is the moral part: can we allow for human life to be extinguished fully auto-
nomously, without a human decision? It can be argued that by launching the drone,
such decision was already made, as such possibility was considered. The problem with
this reasoning is that the possibility of error in the decision process (due to software
error or the hacking of the software) cannot be considered. In specific scenarios, it
can be called collateral damage, but the moral essence remains highly questionable.
The possibility of interfering in the decision-making process should also be examined
here, that is, the question must be asked: what is the risk from cyberspace of a par-
tially autonomous weapon whose handler is not in direct and guaranteed closed (and
secure) connection with the weapon? The simple answer is that if the connection itself
(between the weapon and the operator) can be attacked and/or the control, arming or
detonation is based on partial software (non-mechanical) methods, then the weapon
can be attacked. The success of such an attack strongly depends on the complexity of
the communication systems/software. Thus, the assessing of such vulnerability must
consider the knowledge and experience required for a successful attack.
It is also an open question that if there is death resulting from the operation
of an AI system, who has legal responsibility? An example is the 2017 accident of
a Tesla Model X, in which the vehicle’s partially self-driving system drove the vehi-
cle into a reinforced concrete track separator at a speed of 110 km/h with virtually
no braking. The accident investigation found that there were several faults in the
See www.stm.com.tr/en/kargu-autonomous-tactical-multi-rotor-attack-uav
United Nations, Final report of the Panel of Experts on Libya established pur suant to Security Council Resolution 1973 (2011),
Pub. L. No. S/2021/229.
For the sake of thought, it is worth addressing the question of what would happen if such drones were used not in
themselves but in autonomous swarms.
This paper does not intend to examine the answer to the question posed in part, nor does the ques tion itself belong
primarily to the field of military science.
Following the accident, the driver of the car died due to extreme forces in the collision.
Tesla calls this system “AutoPilot”.
Rebecca Heilweil, ‘Tesla Needs to Fix Its Deadly Autopilot Problem’, Vox, 26 February 2020.
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Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
semi-self-driving system, but in legal terms, the manufacturer never claimed that
the vehicle was capable of driving fully automatically without a driver. Moreover, the
manufacturer explicitly warned that the driver of the vehicle must be able to intervene
at any time to manoeuvre, accelerate or decelerate the vehicle.
7. Domains built on each other
The domains of military operations should also be examined from a perspective of
subordination/superiority.
First, by examining the classical (land, water, air) domains, it can be concluded
that land is a condition for the other two domains, since both sea and air operations
require land – mainly to ensure the flawless operations of supply chains. Both marine
vehicles and aircraft can transport food and fuel required for themselves and their
crews. This self-supply is usually available for a period of a few hours to a few months,
but sooner or later, land will be needed to replenish the stocks.
Cyberspace, which is defined as the fourth domain, cannot be interpreted without
infocommunication systems. Since infocommunication systems also rely very heavily
on land (land-based) components, cyberspace’s reliance on land cannot be questioned.
Space as the fifth domain is inoperable without cyberspace, as spacecraft orbiting
in space require constant communication with terrestrial centres, especially to stay
on orbit accurately. As in space, autonomous vehicles are becoming more common
in the sea and air domains. However, their autonomy is not yet absolute and in all
cases they are equipped with communication capabilities that presume some kind of
wireless network connection. And if they have network connectivity, they are also,
by definition, part of cyberspace.
It is clear, that without classical domains cyberspace cannot be interpreted, and
without cyberspace, space (in its present form) is inoperable, meaning that a proper
attack on classical domains can limit cyberspace and outer space capabilities. The
reverse is also true, i.e. a stand-alone, well-targeted, and successful attack on cyber-
space and space domains can significantly limit operational and civilian capabilities in
traditional domains. Cyber experts will argue that for a successful cyber operation, the
conventional domains are not really required. In a narrow sense, they might be right;
however, on a broader horizon, considering the land components of communications,
the proper intelligence required for a successful operation all lead to a conclusion:
control over land (as a domain) remains a requirement. From another approach, we
can say that there are extremely strong interdependencies between land and cyber
When examining cyberspace and AI systems, it is irrelevant which of the classical domains is consid ered the primary
determinant, especially since the classical domain currently in use will be authoritative due to the duration of the
execution of a cyber operation.
If we examine the theory of offensive weapons deployed in outer space, communication is also necessary since
launching an attack requires some kind of ground control (at least for orbit corrections).
Such connection can be satellite-based, in older systems VLF (Very Low Frequency) can still be utilised.
It is sufficient to attack the control system of navigation satellites (cyberspace) or the navigation satellites themselves
(in space). Of course, such aggression will result in the most severe and immediate counterattack, so the attack clearly
does not worth it. However, it does not change the logic of the basic o peration of domains.
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Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
domains. The same remains valid for the connection between the cyber domain
and AI. So in this context, AI also becomes interpretable as a domain-like realm, as
similarly to cyberspace, independent processes can take place in AI. Such processes
can have severe effects on other official domains.
The order of domains is listed in the chronology of NATO’s adoption of cyberspace
and outer space. Other classifications, such as Ronald Fogelman’s system, designate
space as the fourth and information operations as the fifth domain. Without going
into details, Fogelman’s classification remains partially true considering information
operations. However, the components thereof have considerably changed and cyber
operations (in many cases) are fundamental elements of more comprehensive information
operations. Today the proper nomenclature could be “information realm” (as opposed
to “information operations”) in a domain sense. The problem with “information realm”
is that it is too broad and contains cyber, AI and computer network operations (which
are now cyber operations). From a different perspective, the term “information domain”
would be equal to “conventional domain” – containing land, air and sea. That would
be an oversimplification of domains, which might not serve the purpose of reflecting
actual reality in descriptions. Such a debate is also a prime example of how radical
advances in technology during the course of 15–20 years can transform thinking about
the fundamental domains of state-run, state-sponsored military/security operations.
8. Conclusion
For classical military science, the use of armed force and state-will enforcement are
interdependent and separate areas. With the significant expansion of cyberspace as
a domain and AI, state-will enforcement has received a new and broad set of tools,
the use of which, especially on the offensive side, does not necessarily require the
armed force of a given state.
As a result of operations in these domains, new risks have emerged that funda-
mentally threaten the functioning of a country, as attacks on critical infrastructures
in that country can significantly and permanently limit economic, social processes
and state governance.
It would be important not only for technical and ethical studies to be conducted
in the military application of AI, but also for its consideration to appear on a doctrinal
level. Interdependent decision-making processes, insofar as they are based on AI,
are not merely man-made support systems but can have severe and autonomous
NATO recognised cyberspace as an independent domain on 9 July 2016 at the Warsaw Summit. Space as a domain
was recognised by NATO at the December 2019 meeting of Heads of State and Government.
General, United States Air Force. Chief of Staff of the U.S. Air Force, 1994–1997.
Ronald R Fogelman, ‘The Fifth Dimension of Warfare’, Defense Issues 10, no 47.
Zsolt Haig and László Kovács, Kritikus infrastruktúrák és kritikus információs infrastruktúrák (Budapest: Nemzeti Köz-
szolgálati Egyetem, 2012).
Research concerning AI in the armed forces is extensively performed at the University of Public Service, Faculty of
Military Science and Officer Training. Col. Haig and Col. Négyesi cover different aspects of this field and have numerous
publications on the subject.
Hadtudományi Szemle • 14. évfolyam (2021) 4. szám 15
Kristóf Kralovánszky: Certain Connections between Cyber Operations, Artificial Intelligence…
influence, even at the strategic level. In other words, strategic decisions can be made
on information summarised solely by AI.
Advances in technology have demonstrated that we have gone well beyond
the level where it is sufficient to deal with AI as a narrow part of information ope-
rations. In the early 2000s, cyberspace was seen as a unique blend of information
technology and cybernetics. It was not until 2016 that NATO accepted its existence
at the Alliance level – while the same Alliance already established the Cyber Defence
Centre of Excellence in Tallinn in 2008. For this centre to be established, Estonia had
to suffer the consequences of the 2007 cyberattacks. Just as cyberspace has become
an increasingly integrated part of our lives, AI is becoming the foundation of electronic
decision-making systems. All of this happens by often considering AI just one of the
smaller components of cyberspace or an advanced software.
The lifecycle of technical devices used in defence (especially AI-based systems)
has been significantly reduced – mainly due to the commercially available and
constantly evolving products and services available to adversaries. On the defence
side, we are not necessarily talking about classical depreciation but rather about
forced and technological obsolescence. This represents a major paradigm change
and requires a fundamental shift in thinking on the design and procurement side.
Therefore, responses to threats must necessarily follow the same innovation curve
that appears on the attacker side. Losing out on the pace of development will widen
the gap between the attacker and the defensive side, resulting in defects of defence
capabilities and ultimately in partial incompetence.
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