=Paper=
{{Paper
|id=Vol-3909/Paper_15.pdf
|storemode=property
|title=Modeling of Media Influence on Personal Information Security
|pdfUrl=https://ceur-ws.org/Vol-3909/Paper_15.pdf
|volume=Vol-3909
|authors=Vitalii Savchenko,Halyna Haidur,Svitlana Lehominova,Taras Dzyuba,Oleksandr Laptiev
|dblpUrl=https://dblp.org/rec/conf/iti2/SavchenkoHLDL24
}}
==Modeling of Media Influence on Personal Information Security==
https://ceur-ws.org/Vol-3909/Paper_15.pdf
Modeling of media influence on personal information
security
Vitalii Savchenko1, , Halyna Haidur1 , Svitlana Lehominova1 , Taras Dzyuba1 and
Oleksandr Laptiev2,
1
State University of Information and Communication Technologies, Solomianska street, 7, 03110, Kyiv, Ukraine
2
Taras Shevchenko National University of Kyiv, Volodymyrska street, 60, Kyiv, 01033, Ukraine
Abstract
With the development of information influence technologies, the problem of personal protection from
media information is becoming increasingly important. To study this phenomenon, it is necessary to create
realistic models that would give an opportunity to evaluate the influence of information from the media on
human behavior. The existing socio-cognitive and statistical models are too generalized and therefore
cannot have practical application. The most convenient for research are the models of conformal human
behavior, which can connect the position of the media and the behavior of a person depending on this
position. On the basis of the conformity model, the authors of the article propose a simple probabilistic
model on which they study the nature of media influence on individual behavior. The input parameters of
the model are the a priori attitude of the individual to a certain social phenomenon, the degree of
independence of the individual's thinking, the position of alternative media in relation to the specified
phenomenon, and the degree of the individual's trust in the media. The authors of the article provide a
formalized description of the concept of personal information security, as the difference between the
deviations of an individual's position under the influence of alternative media. The main means of
counteracting the negative influence of the media on personality is the mechanism of changing information
flows between two alternatives. The authors determine the appropriate proportion of media change to
achieve a given level of personal information security, depending on the position of the individual.
Simulation of various scenarios of media flow management confirms the adequacy of the applied model
and indicates that a person with a high level of independence, with a well-thought-out media change
technology, is able to resist most informational influences and, thereby, ensure their own information
security at a given level.
Keywords
media information, information security, personality, personal information security, conformism,
information influence 1
1. Introduction
With the development of technologies, media information has become a powerful influence on a
person's personal security. Cyberattacks, identity theft, and other security breaches are becoming
more common and people need to take preventative measures to protect both their personal
information and their mental state. A person's ability to recognize and counteract the harmful effects
of information increases his resistance to stress and promotes greater confidence in his own actions
and decisions in conditions of constant information pressure. In this aspect, it is necessary to create
realistic models that would make it possible to evaluate the influence of information from the media
on human behavior. Such models can be a useful tool for analyzing individual security risks and
Information Technology and Implementation (IT&I-2024), November 20-21, 2024, Kyiv, Ukraine
Corresponding author.
These authors contributed equally.
savitan@ukr.net (V. Savchenko); gaydurg@gmail.com (H. Haidur); chiarasvitlana77@gmail.com (S. Lehominova);
iwartar@gmail.com (T. Dzyuba); alaptev64@ukr.net (O. Laptiev)
0000-0002-3014-131X (V. Savchenko); 0000-0003-0591-3290 (H. Haidur); 0000-0002-4433-5123 (S. Lehominova); 0000-
0001-6607-2507 (T. Dzyuba); 0000-0002-4194-402X (O. Laptiev)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
196
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
vulnerabilities. This article examines the application of a mathematical model of personal security
under the influence of media information.
2. Problem statement
Personal information security has become a pressing issue in the digital era with the rise of cyber-
attacks, data breaches and other security threats. The impact of media information on personal
security is widely recognized, and various forms of media are used to spread misinformation,
influence individual behavior, and facilitate security breaches. To address these issues, many studies
have investigated the relationship between media information and personal security of an individual.
Previous research has highlighted the importance of personal security in the digital age and the role
that media information plays in shaping it. However, there is a need to choose a mathematical model
that could quantify the impact of media information on individual security.
3. Related works overview
The influence of mass media has long been a subject of study in world science [1 2]. But, reviewing
the scientific literature, there are gaps in the authors' attempts to develop appropriate mathematical
models.
In the article [3], the authors investigated the impact of social networks on privacy and security.
The study found that social media users were more likely to engage in risky behavior, such as sharing
personal information online, when they felt their privacy was at risk. Another publication [4]
investigated the impact of the media on cyber security incidents. Research has shown that media
coverage of cyber security incidents can increase the likelihood of similar incidents in the future.
There are also publications devoted to the connection between media literacy and personal safety.
In particular, in the article [5], the authors investigated the impact of media literacy on students'
ability to prevent security breaches. The study found that students who received media literacy
training were less likely to be victims of security breaches. At the same time, there is a need for a
more complete understanding of the relationship between media information and individual
security.
The article [6] summarizes the empirical data obtained as a result of sociological research and
proposes a model of voter reaction to the influence of mass media during presidential election
campaigns. The main element of the proposed model is the dependence of the number of votes cast
for candidates at various stages of the presidential election on the amount of airtime allocated to
them on state TV channels. Such an approach, although quite realistic, can only be applied after the
elections are over.
In the article [7], the authors analyze the influence of mass media on the mass audience. Although
the authors explore this topic in considerable depth, they do not provide a simple formalization for
evaluating influence processes, which complicates the practical application of the media influence
model. The authors of the publication [8] propose a probabilistic statistical approach for the
development of heuristic mathematical models of human behavior based on its internal
psychological analysis. However, for an adequate assessment of human behavior, it is necessary to
rely on specific actions, and not on internal psychological analysis, the process and results of which
are practically impossible to subject to qualitative and quantitative assessment.
The authors of [9] explore the concept of multi-model thinking, which involves using a set of
models to understand complex phenomena. Multi-model thinking not only increases work efficiency,
but also contributes to success in social life, which allows you to become real experts in assessing
economic and political events. However, the use of the proposed models to formalize the impact of
the results of social research turns out to be quite problematic.
A number of our previous works are devoted to the protection of people in social networks. For
example, in [10] the security parameters of the personal data of an individual were investigated
197
depending on the topology and mutual influence of social network users. In [11 13], the dependence
of information security of an individual in a social network on the influence of social engineering
methods is considered. The work [14] examines the issue of taking information content into account.
The publications [15, 16] analyze various methods of social control as a mechanism of self-
organization, as well as the decision-making process in antagonistic digital communications. At the
same time, the individual in all these works is considered as a passive receiver of information that
does not change the line of behavior depending on the source of information. The issue of the impact
of content on changing the line of behavior of an individual, namely its conformity, remains out of
consideration.
The work [17] analyzes modern mathematical models of conformity, which are investigated by
the methods of probability theory, game theory, and statistical physics. The work also provides
numerous examples of social and economic situations that can be interpreted as manifestations of
herd behavior. However, within the framework of this study, it is unlikely to be limited only to the
variant of herd behavior, which requires the use of other approaches to building a model of media
influence. The paper [18] investigated the construction of a model of the behavior of an individual
who, when making decisions on certain issues, relies on both his own opinion and the attitude of
surrounding subjects (team). Such an approach can be used to create a general model for evaluating
the impact of media on individual behavior. Its advantages are simplicity and accessibility, as well as
the possibility of expansion, since the author offers only a basis that can be supplemented with other
aspects in the future.
The authors of the article [19] develop the model [18] and investigate the complex of mutual
influences on the individual based on the solution of the problem of choice, within the team, which
affects the individual's decision-making and evaluate the role of television in election campaigns.
The state of information security of an individual under the influence of mass media is also
investigated, the dependence of team members on the opinion of other participants and television is
taken into account. This makes it possible to determine the conditions for ensuring a person's
information security. In the following article [20], the author proposes a model of personal
information security based on the concept of probabilistic control of conforming behavior. This
approach makes it possible to explore different strategies for managing the influence of media
information on a person and to choose an appropriate information management strategy that
ensures the necessary level of information security of an individual.
There are other models of conforming behavior [21 22], which deeply explore the psychological
features of a person in their relationship with the features of human character, but without taking
into account the influence of media information. The disadvantage of such models is the complexity
of their application for real assessments of information security.
So, from the conducted consideration, it can be concluded that currently the issue of formalization
of the influence of the media on the behavior of individuals has been studied extremely insufficiently.
The following shortcomings can be noted in the mathematical models proposed by various authors,
in particular:
• Models using a probabilistic statistical approach are overloaded with internal psychological
analysis of the individual, which is difficult to adapt to the influence of the media.
• Models of personal protection in social networks consider a person as a stable recipient of
information without taking into account the degree of its relevance.
• Mathematical models of conformity and conforming behavior are the closest, although they
need improvement for the possibility of using media information in them.
The purpose of this paper is to develop and explore a mathematical model that can provide a
quantitative analysis of the relationship between media information and personal information
security, allowing researchers to develop more effective strategies to promote individual security in
the digital age.
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4. Mathematical model of personal information security
In work [18], the author proposes a model of the behavior of a person who is under the influence of
other people from his environment. The proposed model takes into account: initial beliefs of the
individual; the degree of independence of her thinking and the influence of the environment on the
personality. Thus, the specified model can be used as a basis for a general model for evaluating the
influence of media on individual behavior. When developing a model of conformal behavior of an
individual in [19], the basis is communication with other individuals. This is expressed in the
application of appropriate probabilistic indicators of the influence of the environment on the
individual and the reverse influence of the individual on the environment. In contrast to this
approach, the individual's perception of media information has its own characteristics, in particular,
the individual does not directly influence the mass media. In addition, an individual can perceive
secondary influence, when information from the mass media is transmitted to the individual from
other subjects in his environment. Therefore, the basic model of conforming personality behavior
should be improved taking into account the identified features.
As in the basic model, we will assume that a person, making a decision on this or that issue, is
guided by both his initial beliefs and the attitude of other subjects from his environment to this issue.
As part of our review, collective opinion will include public opinion expressed in the mass media
(Internet channels, social networks, television, radio, etc.). We'll look at events that can be presented
in binary form, such as "support" or "don't support".The mathematical model [20] is based on two
quantitative assessments of the individual's attitude to the new state:
• Personal a priori attitude to a new state (conviction of the individual), which is described by
the probability of readiness of the individual to move to this state (𝐴𝑝𝑟 ) before the influence
of the media.
• Personal posterior attitude to the new state, which is described by the probability of the final
decision to move to the new state (𝑃𝑝𝑜𝑠𝑡 ) after media exposure.
The probabilities 𝐴𝑝𝑟 and 𝑃𝑝𝑜𝑠𝑡 describe exactly the informational component of the process of
transition from the initial to the final state, as they are determined by the influence of the media on
the individual. In the case when the individual is independent in decision-making, he may not be
subject to such influence and then, obviously, his a posteriori attitude will coincide with the a priori
𝐴𝑝𝑟 = 𝑃𝑝𝑜𝑠𝑡 .
Another characteristic that should be taken into account in the future is the degree of
independence of the individual 𝐼𝑛𝑑 , which is defined as the probability that in a specific situation the
individual behaves as independent. If 𝐼𝑛𝑑 = 1, then the individual's decisions do not depend on
media influence. If 𝐼𝑛𝑑 = 0, then we have an absolute dependence, which means an almost
instantaneous change of the initial beliefs of the individual under the influence of the media.
In contrast to the model of conforming behavior [21], in the following work, we will consider
only the change in personality behavior under the influence of the media. So, as was mentioned, in
𝐼𝑛𝑑 =1
a completely independent individual, the posterior probability 𝑃𝑝𝑜𝑠𝑡 coincides with the a priori
𝐼 =1
𝑛𝑑
𝑃𝑝𝑜𝑠𝑡 = 𝐴𝑝𝑟 , i.e. with his beliefs. The posterior probability for a completely dependent individual
𝐼 =0
𝑛𝑑
𝑃𝑝𝑜𝑠𝑡 can be determined based on the following considerations. We will assume that the influence
of each i-th media on a given individual is determined by the number 𝐸𝑚𝑒𝑑𝑖𝑎[𝑖] the probability that
the individual will act as follows from the i-th message of the media. At the same time, we will also
assume that such an influence of the i-th media message on this individual does not depend on the
influence of other alternative media messages. This means that the individual will enter a new state
with probability 𝑃𝑚𝑒𝑑𝑖𝑎[𝑖] . Then the total probability of transition of a completely dependent
individual to a new state will be equal to
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𝐼
𝑛𝑑
𝑃𝑝𝑜𝑠𝑡
=0
= ∑𝑁
𝑖=1 𝐸𝑚𝑒𝑑𝑖𝑎[𝑖] 𝑃𝑚𝑒𝑑𝑖𝑎[𝑖] ,
(1)
where N is the total number of media messages (or sources); ∑𝑁 𝑖=1 𝐸𝑚𝑒𝑑𝑖𝑎[𝑖] = 1 [22] and all
𝐸𝑚𝑒𝑑𝑖𝑎[𝑖] > 0, since a completely dependent individual is affected by any media message.
As you can see, 𝐸𝑚𝑒𝑑𝑖𝑎[𝑖] expresses the degree of influence of media on personality. On the other
hand, taking into account ∑𝑁𝑖=1 𝐸𝑚𝑒𝑑𝑖𝑎[𝑖] = 1, 𝐸𝑚𝑒𝑑𝑖𝑎[𝑖] can also be considered as a distributed level
the personality.
Thus, the posterior probability for an arbitrarily chosen individual can be obtained based on the
formula for the total probability
𝑛𝑑𝐼 =1 𝑛𝑑 𝐼 =0
𝑃𝑝𝑜𝑠𝑡 = 𝑃𝑝𝑜𝑠𝑡 𝐼𝑛𝑑 + (1 − 𝐼𝑛𝑑 )𝑃𝑝𝑜𝑠𝑡 =
(2)
= 𝐴𝑝𝑟 𝐼𝑛𝑑 + (1 − 𝐼𝑛𝑑 ) ∑𝑁 𝑖=1 𝐸𝑚𝑒𝑑𝑖𝑎[𝑖] 𝑃𝑚𝑒𝑑𝑖𝑎[𝑖] .
Formula (2) is a model of the individual's behavior under the influence of the media in general,
with the simplifications that have been adopted. Unlike the model of conforming behavior, this model
takes into account the level of trust in the media and the peculiarities of the information exchange
between the individual and the media.
Given the given parameters (𝐴𝑝𝑟 , 𝐼𝑛𝑑 , 𝑃𝑚𝑒𝑑𝑖𝑎 ) from formula (2) it is possible to determine the
posterior probability (𝑃𝑝𝑜𝑠𝑡 ), which in vector form will have the form
𝑃𝑝𝑜𝑠𝑡 = 𝑨𝑝𝑟 𝑰𝑛𝑑 + (𝑼 − 𝑰𝑛𝑑 )𝑬𝑚𝑒𝑑𝑖𝑎 𝑷𝑚𝑒𝑑𝑖𝑎 , (3)
where 𝑬𝑚𝑒𝑑𝑖𝑎 is a stochastic matrix (𝐸𝑚𝑒𝑑𝑖𝑎[𝑖] ), 𝑰𝑛𝑑 is a diagonal matrix (𝐼𝑛𝑑 ), 𝑼 is a unit matrix,
𝑨𝑝𝑟 and 𝑷𝑚𝑒𝑑𝑖𝑎 are vectors with components 𝐴𝑝𝑟 and 𝑃𝑚𝑒𝑑𝑖𝑎 , respectively.
Personality is constantly under the influence of various media. It is logical to assume that some
media will incline a person to certain decisions, other media, which have an alternative focus, to
alternative decisions. Thus, as can be seen from the previous discussion, the value of 𝑃𝑝𝑜𝑠𝑡 for an
𝑀𝐴𝑋
individual under the influence of different media will vary from some maximum value of 𝑃𝑝𝑜𝑠𝑡 to a
𝑀𝐼𝑁
minimum value of 𝑃𝑝𝑜𝑠𝑡 .
Taking into account the above statements, in general, the model of personal information security
can be formulated as follows
𝑀𝐴𝑋 (𝑡)
∆𝑃𝑝𝑜𝑠𝑡 = 𝑃𝑝𝑜𝑠𝑡 𝑀𝐼𝑁 (𝑡)
− 𝑃𝑝𝑜𝑠𝑡 ≤ 𝐿𝑖𝑚 , (4)
𝑀𝐴𝑋 (𝑡), 𝑀𝐼𝑁 (𝑡)
where 𝑃𝑝𝑜𝑠𝑡 𝑃𝑝𝑜𝑠𝑡 respectively, the maximum and minimum value of 𝑃𝑝𝑜𝑠𝑡 during the
specified time period t; 𝐿𝑖𝑚 is some pre-set spread value of 𝑃𝑝𝑜𝑠𝑡 .
That is, it will be possible to talk about the information security of an individual when condition
(4) is met, namely: the a posteriori probability 𝑃𝑝𝑜𝑠𝑡 of the individual's transition to a new state under
the influence of the information channel of information influence will remain within certain limits
relative to its a priori probability 𝐴𝑝𝑟 .
5. Simulation and discussion of results
To keep 𝑃𝑝𝑜𝑠𝑡 within the given limits 𝐿𝑖𝑚 of the individual, depending on the initial beliefs of 𝐴𝑝𝑟 ,
the degree of independence 𝐼𝑛𝑑 and the level of trust in the channel of information influence 𝐸𝑚𝑒𝑑𝑖𝑎 ,
it is necessary to have one's own strategy for managing media influence. To simplify understanding,
we will consider a person who is under the influence of two alternative media. In many cases the
entire set of media messages can be divided into two opposite groups: "agree" or "disagree"; "positive"
or "negative", etc. Thus, it is possible to group all the media into two opposite groups regarding some
200
high-profile event, which one of the groups will support, and the other will be in opposition to the
first.
For example, we will consider the scenario of an election campaign, when various media support
"their" presidential candidates, while leveling the ratings of their opponents. So, let's take 2
alternative media: Media 1 and Media 2, which broadcast information about the same Candidate X.
Media 1 determines the support of the Candidate X at the level of 0.9 (that is, believes that such a
candidate will win 90% of the vote in the elections). Media 2 determines the support of the same
Candidate X at the level of 0.1 (believes that this candidate will win only 10% of the vote in the
elections).
The individual has his own opinion about Candidate X, which is expressed through his initial
beliefs 𝐴𝑝𝑟 . Also, an individual has his own degree of personality independence 𝐼𝑛𝑑 , which will
determine his ability to be influenced by the media. An individual has the opportunity to choose
between Media 1 and Media 2 in order to stay with his beliefs 𝐴𝑝𝑟 as long as possible (this is the
essence of personal information security to stay with his own views as long as possible without
being influenced by the media). With this approach, the key strategy for ensuring the informational
security of the individual will be the change in media exposure between the two alternatives, which
will satisfy formula (4). We will provide separate graphs and comment on possible options for
implementing the "media change" strategy.
Fig. 1 shows that in the case (𝐴𝑝𝑟 = 0.9, 𝐼𝑛𝑑 = 0), when the individual supports Candidate X at a
level that coincides with Media 1, then keeping him in a state of information security is quite a
difficult task as Media 2 will sway him to its side. As soon as Media 2 sways the individual to its side,
the individual changes the source to Media 1 and now Media 1 will sway him to its side. All this
happens due to the degree of independence of such an individual is zero (𝐼𝑛𝑑 = 0) and therefore any
information polarizes his 𝑃𝑝𝑜𝑠𝑡 , that results ∆𝑃𝑝𝑜𝑠𝑡 = 0.8, which is the maximum value and indicates
the absence of any information security for such an individual.
Consider the case when the individual's initial beliefs differ from the position of Media 1, for
example, with 𝐴𝑝𝑟 = 0.8, and his resistance to informational influence is sufficiently high (𝐼𝑛𝑑 =
0.8). In this case, it can be seen that any influence of Media 2 leads to a change individual's beliefs to
the contrary, but such an influence can be compensated by four inclusions of Media 1 and at the
same time the individual is able to ensure ∆𝑃𝑝𝑜𝑠𝑡 = 0.16 (Fig. 2).
In the case when 𝐴𝑝𝑟 = 0.2, 𝐼𝑛𝑑 = 0.8, the picture will be symmetrical, because in this case our
individual is inclined to the position of Media 2, and at the same time, each influence from Media 1
can be compensated by four influences from Media 2. As in the previous case, the level information
security for an individual is provided at the level of ∆𝑃𝑝𝑜𝑠𝑡 = 0.16 (Fig. 3).
Figure 1: Simulation results at 𝐴𝑝𝑟 = 0.9, 𝐼𝑛𝑑 = 0.
201
Figure 2: Simulation results at 𝐴𝑝𝑟 = 0.8, 𝐼𝑛𝑑 = 0.8.
𝑦𝑖𝑒𝑙𝑑𝑠 𝑦𝑖𝑒𝑙𝑑𝑠
According to general logic, an increase in 𝐼𝑛𝑑 → 1 will lead to a decrease in ∆𝑃𝑝𝑜𝑠𝑡 → 0, which
will indicate the achievement of information security of the individual. So, with (𝐴𝑝𝑟 = 0.7, 𝐼𝑛𝑑 =
0.9) you can see that ∆𝑃𝑝𝑜𝑠𝑡 = 0.08. At the same time, the individual on average needs to change
media in a ratio of 2:1 in favor of Media 1. That is, one inclusion of Media 2 can be leveled by 2 3
inclusions of Media 1 (Fig. 4).
Figure 3: Simulation results at 𝐴𝑝𝑟 = 0.2, 𝐼𝑛𝑑 = 0.8.
202
Figure 4: Simulation results at 𝐴𝑝𝑟 = 0.7, 𝐼𝑛𝑑 = 0.9.
The general dependence of the information security of the individual ∆𝑃𝑝𝑜𝑠𝑡 on 𝐴𝑝𝑟 and 𝐼𝑛𝑑 is shown
in Fig. 5, where it is shown that with the increase of 𝐼𝑛𝑑 , the values of ∆𝑃𝑝𝑜𝑠𝑡 decrease almost linearly
and reach 0 when the value of 𝐼𝑛𝑑 = 1.
At the same time, ∆𝑃𝑝𝑜𝑠𝑡 almost does not change with a change in the a priori beliefs of the
individual 𝐴𝑝𝑟 . In general, this corresponds to the logic of common sense, since the individual's
resistance to external informational influences depends mainly on his internal (innate) qualities or
character traits, and not on the position he occupies in relation to some event. Individual fluctuations
of ∆𝑃𝑝𝑜𝑠𝑡 values, which can be seen in Fig. 5, due to the fact that the indicated indicators are obtained
as a result of simulation.
Figure 5: Dependence of personal information security ∆𝑃𝑝𝑜𝑠𝑡 on 𝐴𝑝𝑟 and 𝐼𝑛𝑑 .
203
The average values of 𝐴𝑝𝑟 for different values of 𝐼𝑛𝑑 are shown in Table 1. As can be seen,
sufficiently low values of ∆𝑃𝑝𝑜𝑠𝑡 < 0.2 are observed at high values of 𝐼𝑛𝑑 > 0.7, which once again
confirms the conclusions made earlier.
Table 1
Average values of ∆𝑃𝑝𝑜𝑠𝑡 depending on 𝐼𝑛𝑑
𝐼𝑛𝑑 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
∆𝑃𝑝𝑜𝑠𝑡 0.80 0.70 0.61 0.52 0.45 0.37 0.29 0.23 0.15 0.08 0.00
As can be seen from the previous discussion, in order to remain with his beliefs, the individual must
manipulate the information from the media by timely changing Media 1 to Media 2 and vice versa,
when these media force the individual to change his beliefs, moving away from their initial value.
Therefore, an interesting question is how often it is necessary to change sources of information to
ensure information security? To investigate this issue, let's turn to the developed model again and
determine the ratio of media change depending on 𝐴𝑝𝑟 and 𝐼𝑛𝑑 . The results of the study are shown
in Table 2.
As can be seen from Table 2, at low values of 𝐼𝑛𝑑 , the change of media is carried out uniformly in an
equal proportion between Media 1 and Media 2. When 𝐼𝑛𝑑 increases, in order to minimize ∆𝑃𝑝𝑜𝑠𝑡 ,
the individual must more often choose the media that is closer in position to the beliefs of the
individual himself. Otherwise, the minimum ∆𝑃𝑝𝑜𝑠𝑡 is not ensured. In the case when the individual
does not have clear initial beliefs 𝐴𝑝𝑟 ≈ 0.5, the media change is carried out proportionally evenly
(in our example 10/10).
Table 2
Dependence of the need to change the media on 𝐴𝑝𝑟 and 𝐼𝑛𝑑 to reach the minimum ∆𝑃𝑝𝑜𝑠𝑡
𝐴𝑝𝑟 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Media Media Media Media Media Media Media Media Media
𝐼𝑛𝑑
1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
0.0 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
0.1 2 18 10 10 10 10 10 10 10 10 10 10 10 10 10 10 13 7
0.2 1 19 7 13 10 10 10 10 10 10 10 10 10 10 13 7 15 5
0.3 1 19 7 13 10 10 10 10 10 10 10 10 10 10 13 7 16 4
0.4 1 19 7 13 10 10 10 10 10 10 10 10 10 10 13 7 16 4
0.5 1 19 6 14 7 13 10 10 10 10 10 10 13 7 14 6 17 3
0.6 1 19 5 15 7 13 10 10 10 10 10 10 13 7 15 5 17 3
0.7 1 19 5 15 7 13 10 10 10 10 12 8 13 7 15 5 18 2
0.8 1 19 4 16 6 14 8 12 10 10 12 8 14 6 16 4 18 2
0.9 1 19 4 16 6 14 8 12 10 10 12 8 14 6 16 4 19 1
1.0 1 19 3 17 5 15 8 12 10 10 12 8 15 5 17 3 19 1
6. Conclusions
In order to ensure the personal information security of an individual, it is necessary to solve the
problem of assessing changes in his behavior under the influence of information from the media. At
the same time, the main goal will be to achieve such an indicator of independence of the individual
𝐼𝑛𝑑 , which would, with any efforts of the media, make it possible to ensure that the resulting value
204
of the posterior probability 𝑃𝑝𝑜𝑠𝑡 remains within the given limits of 𝐿𝑖𝑚 relative to the initial beliefs
of the individual 𝐴𝑝𝑟 . The main mechanism for achieving such a state is the control of the flow of
information coming to the individual from the media.
The model of personal information security studied in this work is based on the concept of
managing information from the media with probabilistic control and evaluation of the individual's
behavior under the influence of the media. This makes it possible to explore various scenarios of
managing the media's information impact on a person and to choose an appropriate information
flow management technology in order to ensure the necessary level of its information security
∆𝑃𝑝𝑜𝑠𝑡 .
Simulation of various scenarios of media flow management confirms the adequacy of the applied
model and indicates that a person with a high level of independence, with a well-thought-out media
change technology, is able to resist most informational influences and, thereby, ensure their own
information security at a given level.
Future research can refine the model by integrating machine learning to predict behavior
dynamics under media influence and analyze content in real-time. Expanding the model to include
cultural and social factors will enable more personalized strategies for managing information flows,
improving individual information security.
Declaration on Generative AI
The authors have not employed any Generative AI tools.
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