=Paper=
{{Paper
|id=Vol-2923/paper20
|storemode=property
|title=Aerial Photographs for Ensuring Cyber Security of Critical Infrastructure Objects
|pdfUrl=https://ceur-ws.org/Vol-2923/paper20.pdf
|volume=Vol-2923
|authors=Volodymyr Barannik,Oleksandr Slobodyanyuk,Andrii Krasnorutsky,Anna Korchenko,Serhii Pchelnikov
|dblpUrl=https://dblp.org/rec/conf/cpits/BarannikSKKP21
}}
==Aerial Photographs for Ensuring Cyber Security of Critical Infrastructure Objects==
https://ceur-ws.org/Vol-2923/paper20.pdf
Aerial Photographs for Ensuring Cyber Security of Critical
Infrastructure Objects
Volodymyr Barannika, Oleksandr Slobodyanyukb, Andrii Krasnorutskyc, Anna Korchenkod,
and Serhii Pchelnikovc
a
V.N. Karazin Kharkiv National University, 4 Svobody sq., Kharkiv, 61022, Ukraine
b
Kamianets-Podilsky Ivan Ohiienko National University, 61 Ohiienko str., Kamianets-Podilsky, 32300, Ukraine
c
Ivan Kozhedub Kharkiv National Air Force University, 77/79 Sumskaya str., Kharkiv, 61023, Ukraine
d
National Aviation University, 1 Lubomir Gyuzar ave., Kyiv, 03058, Ukraine
Abstract
Abstract. The article deals with issues related to the processing of aerial photographs, which
were obtained while using emergency aerial monitoring systems. It shows the actual
involvement of unmanned aerial monitoring systems to prevent, as well as localization of
emergency. Here, the key information is aerial images having different properties, syntactic
and semantic components, and also a plurality of landscaped areas, both of natural origin and
man-made objects. With the help of aerial photos of various processing methods highlighted
important information about the characteristics of semantic objects. A study is an informative
description of aerial photographs as well as processing techniques justified selection of aerial
photographs, at which manage to retrieve images from the most critical information, thereby
reducing the flow of processed and transmitted over the communication channels. It is proved
that dedicated key information from aerial photographs provides operator-interpreter in a
timely manner, accurately make decisions to prevent crises and emergencies.
Keywords 1
Emergency aerial monitoring system, aerial, transform, image blocks, saturation, semantics,
landscaped areas, cybersecurity.
1. Introduction
In today’s world issues associated with the processing of aerial images, obtained through reference
aerial monitoring Unmanned Aerial Vehicles (UAVs) are actual [1–10]. A good example here is the
use of aerial monitoring systems for early warning and emergency response related to natural disasters
(fires, floods, natural disasters), man-made disasters on the territory of the state (explosions at military
arsenals, state-owned enterprises), registration and checking the state of special objects with high-
security level (state-building, transport and energy facilities of national importance).
Aeromonitoring systems are especially important in the protection of critical infrastructure. The
security of a critical infrastructure object is determined by the state of its functionality and continuity
of operation. Ensuring the possibility of identifying factors that could potentially affect the
characteristics of this condition is one of the most important tasks that can be solved with the help of
aerial monitoring systems using UAVs. After all, in the vast majority of cases, critical infrastructure
facilities implement functions and services, the termination or cessation of which can lead to negative
consequences for the population, social and economic status of society, and national security and
defense of the state. Intruders or special forces of enemy countries are likely to attack any of the critical
infrastructures on a daily basis. The efficiency and effectiveness of their detection require the use of
monitoring tools capable of obtaining and processing data in real-time. Such means can be air-based
Cybersecurity Providing in Information and Telecommunication Systems, January 28, 2021, Kyiv, Ukraine
EMAIL: vvbar.off@gmail.com (A.1); slobodyanyuk.olexandr@kpnu.edu.ua (B.2); krasnorutskii.a@gmail.com (C.3); annakor@ukr.net
(D.4); cthutqgxtkmybrjd@ukr.net (C.5)
ORCID: 0000-0002-2848-4524 (A.1); 0000-0001-5195-3053 (B.2); 0000-0001-9098-360X (C.3); 0000-0003-0016-1966 (D.4); 0000-0003-
3007-7474 (C.5)
©️ 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
182
monitoring systems based on the use of UAVs. However, the existing air monitoring systems are not
equipped with onboard subsystems for the analysis of objects located on the surface images obtained
by them. This is due to the limited capabilities of computers installed on aircraft. The task of analyzing
and identifying objects in images is quite time-consuming. An additional complication is the need to
create criteria for evaluating and classifying objects. Based on this criterion, it is possible to classify the
identified objects and analyze the situation around the critical infrastructure object in order to protect it
or prevent an attack on its security perimeter.
In these circumstances, it is necessary to organize a rationale using aerial monitoring systems to
control the elimination of the situation. Also, must be provided a sufficient security level for all data in
this system. Key information at each stage of monitoring, for processing and decision, will be obtained
by aerial photos. On one, aerial required a high degree of saturation of small parts, having significant
amounts reaching approximately 100 Mbps. On the other hand, the onboard equipment of UAV is not
only a means of collecting data but also performs the function of transmitting information via
communication channels on a ground complex in real-time.
Today, the trend of development of UAVs attests to their complex construction . On one bead
complex set of functions implemented as intended, which in the past were not available to them or
perform other forces and means. However, the limitations associated with the lack of size of the
antenna and low power data communications equipment do not allow us to apply the powerful
radios. The consequence of these deficiencies is the problems associated with data transmission
organization. Data channels between UAV and ground complex do not provide timely data
delivery. Not timely delivery of information in the process of aerial monitoring leads to its
obsolescence and loss of relevance. This affects the timeliness of reporting of information
corresponding to the agency, as well as the effectiveness of the tasks in the system using aerial
monitoring of UAVs.
The option of placing more powerful computing subsystems onboard the UAV is not acceptable
as it will increase the mass of the aircraft and reduce its flight characteristics and reduce the ability
to carry additional suspension modules. Transferring the object detection and identification function
to the operator’s flight control panel also has a significant disadvantage. This will lead to the need to
increase the intensity of the information flow of data coming from the UAV to the control panel in
real-time. In the conditions of dense industrial buildings or the presence of obstacles from systems of
electronic warfare of the enemy, it will lead to the emergence of a large number of errors in the
transmission channel. Also, the situation of complete refusal of the management of the aircraft is
probable. Therefore, this solution cannot be applied.
This also raises the question of protection of the transmission channel of aerial photographs obtained
by UAVs and control signals coming to it from the basic ground control point.
Implementation of protection systems against unauthorized access significantly complicates the
complex as a whole and leads to the need to use more advanced computing modules. Their use, as a
rule, increases the total cost of the complex, increases the processing time and delivery of data through
the transmission channel (additional service data is imposed), and even increases the weight of the
aircraft (reduces the possibility of using some other hanging equipment).
One effective solution for expediting communicating information is to reduce the volume of
processed and transmitted over the secured communication channels. This board serves to conduct pre-
processing UAV aerial photographs. However, in this case, it may be distorted or lost part of the useful
information. The resulting aerial image processing can be performed correctly. And this in turn leads
to a decrease in efficiency.
Therefore, to aid decision-making in emergency aerial monitoring system is proposed to apply
rapid detection of critical infrastructure objects onboard UAVs. This will allow us to identify the
most crucial information on the photograph, and thus reduce the flow of unnecessary information
during transmission over communication channels, which are limited to high capacity. Also, it
provides to simplify the task of providing a given level of protection of the work onboard
photographic and control signals sent to the operator of the aircraft on ground control points in
real-time and in the presence of high-density electronic interference and origin.
But it is required to consider restrictions on the computing resources on-board complex, as well as
the degree of wearable limit losses (need to ensure minimization of distortion) [5–12].
Thus, the purpose of the article is an informative description of aerial images with the features
183
of the landscape using aerial monitoring system in emergencies situations; the rationale for the
choice of aerial photos processing technology that will identify objects bearin g basic semantic
saturation, thereby reducing the amount of processed and transmitted over the communication
channels.
2. Main Material
2.1. Aerial Photographs Description
The result of doing emergency aerial monitoring means UAV is to obtain a set of aerial images
with its characteristics. Aerial photographs are characterized by various properties, syntactic and
semantic component images. Aerial photos to be deciphering, depending on the applied
photographic aerial monitoring systems proposed to classify into two groups [2–7] (see Fig. 1).
Aerial photos
Aerial photos that contain a relatively Aerial containing visual images, differ
familiar to the eye image objects significantly from the visual images of real
objects
Figure 1: Aerial photos classification
1. Aerial photos that contain a relatively familiar to the eye image objects. The image is similar
to the one that is visually observed from an unmanned complex. They are black and white and color
aerial photographs.
2. Aerial containing visual images differ significantly from the visual images of real objects.
These include multispectral aerial photography, infrared (heat), and laser aerial photographs. It is
obvious that such uniformity will landscape the area of the area (see Fig. 2).
Offered their description for the presentation of aerial photographs:
1. On the concept of the information in question.
2. On the structural description.
From the standpoint of the structural description, aerial photographs contain:
1. The scope of key facilities for decryption.
2. The scope of the landscape.
And the region of the key objects to decrypt plays an important (pivotal) role. The purpose of the
decryption in this area is the identification of the object of interest.
The main method of extracting information from aerial photographs is their interpretation, the
disclosure of diverse content which contains information about the area. The main complex of
measures for photographic interpretation is carried out on the ground together with the help of the
operator-interpreter.
Depending on the tasks to be solved during the interpretation of aerial photographs, are two types of
decoding: general geographical and sectoral.
In turn, the general geographic interpretation of aerial photographs has been involved in the
preparation of the generalized information on the Earth’s surface and includes two types: topographic
and landscape.
Topographical interpretation of aerial photographs carried out in order to identify, recognize, and
characterization of objects that should be represented on the maps when they are drawing up or
updating. When decoding the landscape—the goal is regional or typological zoning areas.
Sector interpretation of aerial photographs is sufficiently numerous and conducted by various
organizations to address their departmental objectives (military, forestry, geology, agriculture,
surveying, etc.).
184
Depending on the complexity and composition of objects located on aerial photographs, objects are
divided into simple and complex.
Simple objects are called individual natural or artificial objects (facilities, education), located on
land or water and operating a particular function (tank, airplane, ship, building, tree, grass, etc.).
homogeneity terrain objects
of the topography
Figure 2: Aerial photographs with the drone UAV: 1–5 corresponds to the agricultural landscape;
6–8 corresponds forestry, industrial, and landscape settlements; 9–12 terrain objects that need to be
identified
Complex objects are called natural or artificial systems, occupy considerable space on the size, the
specific operating functions, and consist of a plurality of identical or different simple objects that are in
a particular relationship.
Military objects decryption is complex objects (troops, ships (vessels), submarines, underwater
mines, and networking boom, military installations, military and industrial facilities, area) as a rule.
In the process of deciphering aerial images, the following interpretive features of objects (Fig. 3):
Total direct.
Individual (private) attributes of object types.
Group.
Indirect (logical).
Complex identification (unmasking) signs.
When the decoding of images by the operator, the information it receives through the visual
analysis of the screen image. The interpreter perceives primarily spatial information (often about
the quantitative characteristics of the operator does not know). In this case, the brightness
differences it estimates at a high level. In addition, the operator uses the decrypted and ot her
characteristics: the shape of the image; image size; tone image; shadow image; feature location; a
sign of activity.
185
Decryption features
General direct Individual
(physical) Group
(private)
Indirect
Integrated
(logical)
Figure 3: Basic decryption features
The shape and dimensions of the image are the most important information for decoding, as in the
first place most of the objects are identified by their shape and size. However, the identification of
objects on aerial photographs depends on the consideration of all the decrypted signs in general. There
is a direct relationship between the decrypted signs.
Thus, the systematization of the entire set of objects encountered in decoding images is provided.
Therefore, the interpreter, the operator has the opportunity to operate more general categories than a
single object (type), if necessary [13–21].
The area of the landscape plays a supporting role to decrypt. Here the focus is on the texture
areas. We will be called the homogeneous areas of land under the landscape within which the rocks,
terrain, climate, water, soil, vegetation, fauna constitute interdependent and interrelated unity. The
advantage is that most of the aerial photos take natural objects under the guise of areas of
vegetation. In order to solve the problem of the processing of such texture areas, you must first
reduce the search area of the object. It is obvious that those are the areas of uniformity of the
landscape areas.
Landscapes combined into certain groups – are classified. This takes into account their origin
and history of development, the relationship between components (between human deposits soils,
climate, vegetation, topography and moisture conditions, and others.) As well as the level of
influence on their business. The classes are combined landscapes with similar symptoms relief. For
example, in Ukraine, there are two classes of landscapes: plains and mountains. Therefore, the
concept of “homogeneity” of the landscape dialectically combined with the idea of its diversity
Let us consider the texture areas of aerial photographs as the most important parts of an aerial
photograph.
2.2. Presentation of the Texture Areas of Aerial Photographs
Aerial photographs are a lot of texture areas as natural characters, and man-made objects. It is
proposed to classify the texture area. Examples of artificial and natural textures are in Fig. 4.
The texture can be divided into artificial (see Fig. 4a) and natural (see Fig. 4b).
The artificial texture is this structure of graphic characters arranged on a neutral background.
Such signs may be segments of lines, dots, stars, or characters. Natural texture is implied in their
name, or an image of natural scenes containing almost periodic structure. Examples include photos
of brick walls, tile roofs, sand, grass, etc. Further analysis is limited to the natural texture textures.
Patterns describe a very broad class of objects. For example, a brick wall—consists of identical
picture elements. Their scale and rotate the image changes on a relatively simple law. The movement
corresponds to a change-view shooting. A more complex pattern is composed of a limited number of
quasi-randomly arranged elements of the plane. Texture classification is given in Fig. 5.
These flat textures include text on a sheet of paper. Qualitatively, the texture can be divided into
fine-grained, coarse-grained, smooth, granular, undulating. This division is based on signs basic
primitives or spatial interaction therebetween.
186
TEXTURE CLASSIFICATION
Artificial Simple Coarse Strong
texture texture texture texture
Natural Complex Granular Weak
texture texture texture texture
Undulating
texture
Smooth
texture
Figure 4: Examples of artificial (a) and natural (b) textures
Figure 5: Texture classification
According to the degree of interaction of the basic elements distinguish weak and strong texture.
The weak interaction spatial textures nonderivative elements are small. To distinguish such
textures, it is sufficient to determine the repetition rate of a non-derivative element in a local area
of the image. The strong texture is those in which the spatial interaction is not random. Such a
variety of textures indicates the need for the development and application of various processing
methods of texture areas in aerial photographs.
187
With the help of various image processing techniques, we can identify the most relevant information
on the characteristics of semantic objects. In the future, information about objects is transmitted while
maintaining the highest information content to the next phase efficiently transmit information with the
least distortion.
2.3. The choice of aerial photography processing technology
Among the processing methods of various types of data (text, images, video, sound) occupies a
special place in image processing [4]. The use of image processing methods is based on the fact that,
firstly, it is the first area where the user operates a large number of files that you want to compress, and
secondly, there is first found data compression with partial information loss. However, the analysis of
existing image processing methods (JPEG, JPEG2000) revealed the following problematic
disadvantages:
Keeping uniform picture elements does not consider the semantic load of photograph fragments.
Reducing the image resolution violates the achievement of the required level of detail of objects
of aerial monitoring.
The achievement of the required level of information is provided in case of loss of the entire
picture.
The concept of the algorithms of existing image processing techniques is based on a preliminary
segmentation of images with specified dimensions [4–6]. Generally used blocks of standard size N×N,
so the image is processed block by block. Block conversion has low requirements for memory and is
suitable for processing the residual image obtained by block-based motion compensation. Technology
discrete cosine transform (DCT) is one of the most frequently used in image processing. The use of
orthogonal transformation based on the discrete cosine transform DCT, coefficients form arrays
(component) conversion—transformants. Further components transformants were treated as weights,
which is necessary to calculate the basic image, that would get the original picture. The image of
radiation as a result of the aerial photograph consists of texture and informational pieces. It is the texture
of the image that must be present in the spectral space based on the discrete cosine transform DCT.
To perform processing onboard aerial photographs UAV will be the most significant structural
features of the image: the contour, texture, and homogeneous field. However, the interpreter-operator
may be interested in the picture, not all but only certain objects. Therefore, this processing technology
is necessary to use aerial photographs, which will be able to extract from the images the most crucial
information at a minimum expenditure of computing resources.
Thus, the use of an efficient method of processing images onboard provide a reduction in the volume
of transmitted information; improving the quality of homilies (restored) aerial images (which will
properly recognize and distinguish different objects meaningful fragments on an aerial photograph);
reduction of time-consuming to analyze and forecast the situation. This will, in turn, increase the speed
of adjusting information relevant departments but will also increase the efficiency of tasks in an
emergency aerial monitoring system using UAVs.
3. Findings
1. Spend an informative description aerial photo view of features of the landscape. It was revealed
that the landscape plays a supporting role in the processing and decoding, which focuses on the textured
areas.
2. The description of the aerial photos of the concept of the information in question and on the
structural description. It turned out that from the perspective of the structural description, aerial
photographs contain a region key to decrypt objects and landscape the area.
3. To aid decision-making using emergency aerial monitoring systems proposed to use aerial
imagery processing technology onboard UAV), namely the discrete cosine transform. Justified selection
processing technology aerial photographs in which manage to identify the most critical information,
thereby reducing the amount of data to be processed, as well as improve quality teachings (recovered)
aerial photographs.
188
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