=Paper=
{{Paper
|id=Vol-2392/paper1
|storemode=property
|title=Method of Informational and Psychological Influence Evaluation in Social Networks Based on Fuzzy Logic
|pdfUrl=https://ceur-ws.org/Vol-2392/paper1.pdf
|volume=Vol-2392
|authors=Andrii Gizun,Vladyslav Hriha,Maria Roshchuk,Yaroslav Yevchenkoand,Zhengbing Hu
|dblpUrl=https://dblp.org/rec/conf/coapsn/GizunHRYH19
}}
==Method of Informational and Psychological Influence Evaluation in Social Networks Based on Fuzzy Logic==
https://ceur-ws.org/Vol-2392/paper1.pdf
Method of Informational and Psychological Influence
Evaluation in Social Networks Based on Fuzzy Logic
Andrii Gizun1 [0000-0002-2974-6987], Vladyslav Hriha1 [0000-0002-1408-5805],
Maria Roshchuk1 [0000-0003-3631-125X], Yaroslav Yevchenko2 [0000-0002-2385-2658] ,
and Zhengbing Hu3[0000-0002-6140-3351]
1
National Aviation University, Kyiv, Ukraine
2
Institute of Special Communication and Information Security of National Technical Universi-
ty of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine
3
Central China Normal University, Wuhan, China
andriy.gizun@gmail.com, gsmgrey1@gmail.com,
roshchukmv@gmail.com, evchenkoyaroslav29@gmail.com,
hzb@mail.ccnu.edu.cn
Abstract. Recent years number of influences on the information environment
of the states has been increased by non-military methods, which is due to the
high level of development of information technologies and social engineering.
Information and psychological influences become extremely widespread, as ev-
idenced by the publications of the advanced countries where information securi-
ty issues are discussed in the context of information and psychological influ-
ences. The main areas that become the goals of such influences are economic,
military, political, and the means through which they are implemented, mainly
media, social networks. Obviously, for effective counteraction, timely identifi-
cation and identification of the impact is necessary. However, an equally im-
portant task is to clearly and accurately assess possible destructive effects,
which leads to informational and psychological interference. There have been
described the processes of information confrontation in the aspect of its psycho-
logical component. The developed method can be used in information and psy-
chological security, in particular to prevent information and psychological in-
fluence on the individual and social group, effective implementation of coun-
termeasures. The method of evaluation of informational and psychological in-
fluences and the corresponding structural solution of the system of evaluation of
information and psychological influences, which, by processing fuzzy identify-
ing parameters, allows us to assess the destructive effect of informational and
psychological influences and create such systems for fuzzy environment.
Keywords: Model, Informational and Psychological Influence, Methods of In-
formational and Psychological Influence, Evaluation, Fuzzy Logic.
1 Introduction
Information has become an integral part of the activity in the modern environment.
Modern external and internal policies are impossible without taking into account and
using effective forms of informational and psychological confrontation. In recent
years, the number of influences on the information environment of the states has been
increased by non-strain methods, which is due to the high level of development of
information technologies and social engineering. Information and psychological in-
fluences become extremely widespread, as evidenced by the publications of advanced
countries where information security issues are discussed in the context of infor-
mation and psychological influences. The main areas that become the goals of such
influences are economic, military, political, and the means through which they are
implemented, mainly media, social networks, global computer networks, rumors, etc.
Obviously, for effective counteraction, timely identification and identification of in-
fluence is necessary. However, an equally important task is to clearly and accurately
assess of the possible destructive effects, which leads to information and psychologi-
cal intervention. In this regard, the actual task is to develop a system for assessing the
destructive actions of information and psychological influences.
2 Modern expert evaluation methods
The role of expert methods assumes special importance during the period of unstable
development of informational, social, economic and other processes that directly or
indirectly affect the activity of public administration bodies and local governments.
Thus, the expert systems are actively implemented in priority tasks [1], risk identifica-
tion and management [2], various tasks of information systems option [3], for the
detection and evaluation of critical situations [4] etc.
The basis of such systems, besides the actual knowledge created by experts, is the so-
called heuristic or production rules [3, 5]. Under such circumstances, a high degree of
uncertainty in the environmental factors influence is a defining attribute, and therefore
an acceptable accuracy of results cannot be provided by any statistical or other for-
malized methods, no matter how perfect they are [3].
Expert methods are intended to predict qualitative and quantitative characteristics, the
development of which is not completely or partially subject to mathematical formali-
zation due to the lack of sufficient and reliable statistics. The core of expert forecast-
ing method is based on qualified specialists assessments on a specific problem (ex-
perts or groups of experts), formed according to the certain rules for problems solving
or forecasts development, the conclusions are drawn about the development paths of
the forecasting object.
Among the expert techniques there are two main groups distinguished: quantitative
and qualitative. Quantitative methods of expert technologies are based on the logical-
mathematical and statistical methodologies application for generalizing expert opin-
ions, testing statistical significance of the assessment results, confirming the refuta-
tion of the assessment quality in general.
Similar expert approaches were set up to create decisive rules relating to the attacker
detection in the information-communication networks and systems [6-10] and in the
method of criticality level assessment as the emergence result of the information secu-
rity incidents [11].
3 Method of detection and identification of informational and
psychological impact
During the modern warfare, the following classification can be made:
1) methods aimed at people who perceive the information critically:
─ change of opinion by persuasion;
─ psychological isolation of the object;
─ coercion;
─ propaganda.
2) methods aimed at people who perceive the information uncritically:
─ misinformation;
─ propaganda;
─ change of sights by suggestion;
─ infection;
─ manipulation;
─ reframing [12].
As we can see, there is a certain imbalance among the methods, which are directed at
people who perceive information uncritically in most cases. This situation is due to
the fact that it is much easier to achieve a result, to carry out an attack, if the attacker's
actions are aimed at non-critical thinking, since they will bypass a certain "psycholog-
ical shield" of a person.
Propaganda is attributed to both groups, because of the variety of means, it is evident
that its use is equally effective for all people [13].
Concepts and classifications regarding information psychological impact analysis has
shown that today there is no single classification that would cover all aspects and
characteristics of its implementation during the information warfare [13].
In the course of the research, the following evaluation parameters of the informational
and psychological influences were identified: CSA – «Completeness and strength of
argument», CGN – «Consistency with the norms of general public opinion», PR –
«Public reaction», GAF – «Growth of the anxiety factor», VD – «Velocity of distribu-
tion», NAT – «Number of affected targets».
The standard values were constructed in accordance with [10-12].
For the CSA parameter, the following linguistic estimates are: {low (L), medium (M),
high (H)}. Intervals for defining reference values = {[0-20], [21-40], [41-60]} inter-
vals of time.
After the operations we will form the following terms of the linguistic variables for
this parameter:
L = {0/0,33; 1/0,33, 0,63/0,75; 0,43/1; 0/1},
M = {0/0,33; 0,22/0,33; 1/0,75; 0,57/1; 0/1},
H= {0/0,33; 0,33/0,33; 0,75/0,75; 1/1; 0/1}.
For the CGN parameter, the following linguistic estimates are typical: {unmatched
(U), medium agreed (M), agreed (A)}. Intervals for determining reference values =
{[0-33], [34-66], [67-100]} percent.
After the operations we will form the following terms of the linguistic variables for
this parameter:
U = {0/0,33; 1/0,33; 0,92/0,66; 0,4/1; 0/1},
M= {0/0,33; 0,35/0,33; 1/0,66; 0,07/1; 0/1},
A = {0/0,33; 0,1/0,33; 0,44/0,66; 1/1; 0/1}.
For the PR parameter, the following linguistic estimates are: {small (S), medium (M),
high (H)}. Intervals for determining reference values = {[0-33], [34-66], [67-100]}.
After the operations we will form the following terms of the linguistic variables for
this parameter:
S = {0/0,33; 1/0,33; 0,89/0,66; 0,36/1; 0/1},
M = {0/0,33; 0,7/0,33; 1/0,66; 0,27/1; 0/1},
H = {0/0,33; 0,3/0,33, 0,56/0,66; 1/1; 0/1}.
For the GAF parameter, the following linguistic estimates are: {slow (S), medium(M),
high (H)}. Intervals for determining reference values = {[0-33], [34-66], [67-100]}
percent.
After the operations we will form the following terms of the linguistic variables for
this parameter:
S = {0/0,33; 1/0,33, 0,78/0,66; 0,6/1; 0/1},
M = {0/0,33; 0,27/0,33; 1/0,66; 0,5/1; 0/1},
H = {0/0,33; 0,18/0,33; 0,44/0,67; 1/1, 0/1}.
For the VD parameter, the following linguistic estimates are: {slow (S), medium (M),
high (H)}. Intervals for determining reference values = {[0-33], [34-66], [67-100]}
percent.
After the operations we will form the following terms of the linguistic variables for
this parameter:
S = {0/0,33; 1/0,33, 0,91/0,66; 0,75/1; 0/1},
M = {0/0,33; 0,54/0,33; 1/0,66; 0,33/1; 0/1},
H = {0/0,33; 0,23/0,33; 0,73/0,67; 1/1, 0/1}.
For NAT characteristic parameter such linguistic assessment {low (L), medium (M),
high (H)}. Intervals for determining reference values = {[0-33], [34-66], [67-100]}.
After the operations we will form the following terms of the linguistic variables for
this parameter:
L = {0/0,33; 1/0,33, 0,57/0,66; 0,33/1; 0/1},
M = {0/0,33; 0,5/0,33; 1/0,66; 0,56/1; 0/1},
H = {0/0,33; 0,17/0,33; 0,36/0,66; 1/1, 0/1}.
For the DR parameter, the following linguistic estimates are: {short-term (S), medi-
um-term (M), long-term (L)}. Intervals for determining reference values = {[0-33],
[34-66], [67-100]}.
After the operations we will form the following terms of the linguistic variables for
this parameter:
S = {0/0,33; 1/0,33, 0,95/0,66; 0,78/1; 0/1},
M = {0/0,33; 0,42/0,33; 1/0,66; 0,39/1; 0/1},
L = {0/0,33; 0,13/0,33; 0,4/0,66; 1/1, 0/1}.
Let’s represent the calculated reference values in the form of graphs (see Помилка!
Джерело посилання не знайдено.) [13].
In the further, we calculate the for each estimation parameter. At this stage, an as-
sessment is made of the criticality of the impact of each valuation parameter and their
respective ranking. We apply for this method a quantitative pair comparison with the
definition of the square root, which is a kind of method of quantitative pair comparison.
Fig. 1. Graphic representation of fuzzy values. Completeness and strength of argumentation
Fig.2. Graphic representation of fuzzy values. Fig.3. Graphic representation of fuzzy values.
Consistency with public opinion standards Public response
Fig.4. Graphic representation of fuzzy values. Fig.5. Graphic representation of fuzzy values.
Anxiety rising Spread rate
Fig.6. Graphic representation of fuzzy values. Fig.7. Graphic representation of fuzzy values.
Number of affected targets Duration
Pair comparison is the procedure for setting preferences options by comparing all
possible pairs and further streamline object on the basis of comparison [18]. The
paired comparison method is one of the most widely used expert procedures for de-
termining the relative weights of objects.
The basis is the comparison of each of the table parameters and the formation of the
matrix of the pair comparison A aij , where aij selected according to experts on a
scale of relative importance: 1 - alternatives are equally important, 3 - moderate ad-
vantage of one parameter over another, 5 - significant advantage of one parameter
over another, 7 - significant advantage (convincing evidence available), 9 - obvious
advantage of one of the parameters; 2, 4, 6, 8 - intermediate solutions.
The expert fills the locations of the comparison table of the factor with itself gives a
unit. In the first location of the first line, the expert writes a unit, in the second - the
result of a comparison of the first factor with the second, in the third - the result of a
comparison of the first factor with the third, etc. Moving to the second line, the expert
writes in the first location the result of the comparison of the second factor with the
first, in the second - the unit, in the third - the result of comparison of the second fac-
tor with the third, etc. [19].
Next, we calculate the weight coefficients according to the expression
i n i 1 aij , where i 1, I , I is number of evaluation parameters, in this case 7.
I
After that the valuation of the obtained coefficients is carried out according to the
formula: i i / ( iI1i , so that
i 1i 1 .
I
Consider an example of determining the importance coefficients for the predeter-
mined valuation parameters (Table 1). The expert evaluates the importance of each of
them in comparison with the other and puts the information in the table. The coeffi-
cients of importance are calculated and their rationing is carried out. The result of a
pair wise comparison of the estimated parameters of informational and psychological
influences Pi
Table 1. The result of a pair wise comparison of the estimated parameters of the IPI Pi
i\i’ P1 P2 P3 P4 P5 P6 P7 P8 i i
P1 1 5 2 1/5 1/7 3 4 6 1,45 0,15
P2 1/5 1 ¼ 5 5 ¼ 1/3 1/2 0,69 0,07
P3 5 1/5 7 1 1/5 4 5 2 1,65 0,17
P4 7 1/5 5 5 1 5 6 3 2,73 0,29
P5 1/3 4 ¼ ¼ 1/5 1 ¼ 5 0,61 0,06
P6 ¼ 3 2 1/5 1/6 4 1 7 1,04 0,11
P7 1/6 2 3 ½ 1/3 1/5 1/7 1 0,5 0,05
8,48 0,92
The next step is to conduct a ranking of the estimated parameters on the calculated
and normalized factors of importance. As a result of calculations, the parameter
«Growth the factor of anxiety» gets the highest score, and therefore, according to the
expert, is the most priority among the other parameters (Table 2).
Table 2. Ranking of valuation parameters by factors of importance
Estimated parameter, Pi Coefficient of
Importance
Growth the factor of anxiety 0,29
Public reaction 0,18
Completeness and strength of argument 0,16
Number of affected targets 0,11
Associations that cause the source of information 0,08
The problem of assessing the level of criticality of informational and psychological
influence as one of the processes of providing informational and psychological influ-
ence is determined by the fact that its occurrence and development are difficult to
predict (and often not even predictable), that is, we are dealing with an event in an
unclearly formalized space. In addition, there are no generally accepted criteria for
assessing the level of criticality, most of them have different nature (including clear
and unclear) and mathematical properties, which makes it impossible to use most of
the currently known estimation methods to the general set of these criteria. Therefore,
the formation of parameters and the development of methods for assessing the level of
criticality of informational and psychological influence and the methods for its identi-
fication is an relevant task. The method uses the following methods of fuzzy logic as
a method of linguistic terms using statistical data (MLTS) - for constructing reference
values of parameters and evaluation standards, linear approximation by local maxima
(LALM), generalized Heming’s distance (DH) - for processing fuzzy data and con-
ducting operations of fuzzy logic. In addition, expert methods of evaluation and rank-
ing are used: the method of average grades (AG).
The next step is to calculate the overall assessment of the criticality of the situation.
Initially, taking into account the specific methods of information and psychological
impact, the low frequency is formed:
E
LSCi ( L )
e 1
e e (1)
The current low frequency is compared with the reference standard by one of the
known methods of comparison of the low frequency. For these purposes, we use the
method of forming the -- level nominalization of the low frequency [16] and the
method for identifying the terms [14]. The procedure is to calculate nominalized
(transformed) standards and levels. The definition of the generalized Heming’s dis-
tance is carried out then. The criterion for LCS compliance with one of the terms of
the benchmark is the smallest Heming distance.
At the final stage, visualization of the results takes place. In addition, in order to bet-
ter reflect the criticality of the IPCC, it is proposed to display the criticality parame-
ters using the critical indicator. To do this, the appropriate Le parameters should be
pre-defused. The most expedient in this case is the application of the method of the
center of gravity, by which the LF is converted into a clear by the formula:
q q
L 100 (
i 1
X Lq ( xLq ) / ( x ))
i 1
Lq (2)
where q is number of LOAs. A case where the values of individual parameters are
calculated directly without the use of expert methods is possible. In this case, they are
displayed on the indicator by histogram. The development of the method reflects a
new approach to solving the problem of assessing information and psychological
influence. The method is based on fuzzy logic. During its implementation there are
several stages, which are aimed at determining the reference and current values of a
certain information space for the detection of information and psychological influ-
ence. A special feature is the provision of the information and psychological influence
evaluation process, which will be useful in improving the effectiveness of the devel-
opment and implementation of countermeasures.
4 Experimental study of the proposed method
We use the example of the political anti-advertising campaign of the election compa-
ny P. Poroshenko - the video "50 shades of Poroshenko", which was shown on the 1 +
1 channel before the first round of presidential elections in Ukraine [21]. The video
tells about corruption schemes headed by Petro Poroshenko, but not a single concrete
fact was given, which indicates this. The video and individual cuts from it, the infor-
mation was actively disseminated to the official page of the TV channel 1 + 1, affili-
ated with it pages, hostile to the presidential candidate by public groups, as well as
networks of bots on the social network Facebook. Previously, the following method
of information and psychological influence was identified and identified as "Manipu-
lation". Identifying parameters of this method are CSA "Completeness and Strength
of Argumentation", CGN "Consistency with Common Public Opinion Standards",
GAF "Anxiety Rise".
By expert comparison, coefficients of importance for the estimation parameters "Ma-
nipulation" were established. Thus, the following coefficients were obtained for the
importance of fuzzy estimation parameters: Ω 1 = 0,115; Ω2 = 0.333; Ω3 = 0.552.
The measured and analytical data are entered in the table and after the phasation pro-
cess the value of the estimating parameters is determined and the index of the level of
criticality in the fuzzy form is calculated, which then translates into a clear form after
the dephasing, and the results are displayed on the indicator of the criticality of the
situation. In Table 3 the results of critical assessment of "Manipulation" in the social
network Facebook about the video "50 shades of Poroshenko" are given.
Table 3. Evaluation results "Manipulation"
Parameter Importance Fuzzy number characterizing Declassified
factor parameter value value
CSA 0,115 {0/0,33; 0,75/0,75; 1/1} 89
CGN 0,333 {0/0,33; 1/0,66; 1/1} 83
GAF 0,552 {0/0,33; 0,44/0,66; 1/1} 90
To reflect the level of criticality of the situation in a linguistic form, the procedure for
determining the Heming distance between the terms of the estimated benchmark and
the level of LCS is carried out. Having carried out necessary calculations of Heming
distance, with the help of SOKS received that the current level of criticality situation
"High". In addition, the assessment was carried out at various stages of information
and psychological impact, which enabled to show the dynamics of the situation and
assess the adequacy of the countermeasures involved. Figure 1 shows an indicator of
the criticality of the situation in the development of the IPV for "Manipulation. The
overall criticality level is 88.
0 20 40 60 80 88
Fig.8. A figure caption is always placed below the illustration. Short captions are centered,
while long ones are justified. The macro button chooses the correct format automatically.
5 Conclusions
The system of evaluating destructive actions of informational and psychological in-
fluence was developed in the work to solve the problem of destructive effects of in-
formational and psychological influence, which can be used in a weakly formalized
environment close to real conditions. To achieve the goal were performed the follow-
ing tasks:
There was made the analysis of the concept of informational and psychological influ-
ence, its place in the modern information environment was determined, the main
methods and methods of implementation of informational and psychological influence
were investigated and the existing methods of estimating informational and psycho-
logical influence were analyzed. This has made it possible to find that there is no
generalized and sufficiently universal of informational and psychological influence of
evaluation system, and, on the basis of existing highly specialized systems, identify
the shortcomings that most need to be finalized.
The method of carrying out an evaluation of informational and psychological influ-
ence destructive actions is developed. All the deficiencies of existing evaluation sys-
tems identified because of the analysis are taken into account. The most universal
estimation parameters are determined. This method is based on quantitative methods
of expert evaluation, which gives advantages in the absence of the need to collect
large amounts of statistical data and clear formalization of the current situation.
The structure of evaluation of destructive of informational and psychological influ-
ence actions is developed, which allows estimating the level of destructive informa-
tional and psychological influence actions in a fuzzy environment close to real condi-
tions. The scheme of the architecture of the system is presented, which allows more
detailed presentation of the modules and processes with which they interact, input and
output data to each of the blocks and modules.
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