Table Of ContentLecture Notes in Networks and Systems 152
Mykhailo Ilchenko
Leonid Uryvsky
Larysa Globa Editors
Advances in
Information and
Communication
Technology and
Systems
Lecture Notes in Networks and Systems
Volume 152
Series Editor
Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences,
Warsaw, Poland
Advisory Editors
Fernando Gomide, Department of Computer Engineering and Automation—DCA,
SchoolofElectricalandComputerEngineering—FEEC,UniversityofCampinas—
UNICAMP, São Paulo, Brazil
Okyay Kaynak, Department of Electrical and Electronic Engineering,
Bogazici University, Istanbul, Turkey
Derong Liu, Department of Electrical and Computer Engineering, University
of Illinois at Chicago, Chicago, USA, Institute of Automation, Chinese Academy
of Sciences, Beijing, China
Witold Pedrycz, Department of Electrical and Computer Engineering,
University of Alberta, Alberta, Canada, Systems Research Institute,
Polish Academy of Sciences, Warsaw, Poland
Marios M. Polycarpou, Department of Electrical and Computer Engineering,
KIOSResearchCenterforIntelligentSystemsandNetworks,UniversityofCyprus,
Nicosia, Cyprus
Imre J. Rudas, Óbuda University, Budapest, Hungary
Jun Wang, Department of Computer Science, City University of Hong Kong,
Kowloon, Hong Kong
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Mykhailo Ilchenko Leonid Uryvsky
(cid:129) (cid:129)
Larysa Globa
Editors
Advances in Information
and Communication
Technology and Systems
123
Editors
Mykhailo Ilchenko LeonidUryvsky
Igor SykorskyKyiv Polytechnic Institute Igor SykorskyKyiv Polytechnic Institute
National Technical University of Ukraine National Technical University of Ukraine
Kyiv, Ukraine Kyiv, Ukraine
Larysa Globa
Igor SykorskyKyiv Polytechnic Institute
National Technical University of Ukraine
Kyiv, Ukraine
ISSN 2367-3370 ISSN 2367-3389 (electronic)
Lecture Notesin Networks andSystems
ISBN978-3-030-58358-3 ISBN978-3-030-58359-0 (eBook)
https://doi.org/10.1007/978-3-030-58359-0
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Preface
This volume is a collection of the most important research results in fields of
Information, Telecommunication and RadioElectronics Technologies provided by
different group of researchers from Ukraine in collaboration with scientists from
differentcountries.Theauthorsofthechaptersfromthiscollectionpresentin-depth
extended research results in their scientific fields.
The volume consists of three parts.
Part I Modern Challenges in Information Technologies deals with various
aspects to the analysis and solution of practically important issues of information
systems in general, contains an overview of global trends for the development of
informationandcommunicationtechnologies,aswellasprogressionfrombigdata
tosmartdata,developmentofcloud-basedarchitecture,practicalimplementationof
Internet of things (IoT) cryptanalysis, biometric cryptosystems, realization of bio-
metric authentication, fundamentals of information and analytical activities,
including scientific and educational portals, in particular.
Part II Modern Challenges in Telecommunication Technologies contains
original works dealing with many aspects of construction, using research and
forecasting of technological and services characteristics of telecommunication
systems.
The presented studies of this part cover a wide range of telecommunication
technologies, including multigigabit wide area networks, wireless communication
systems,multiservicetransmissionsystems,aswellasin-depthaspectsofthestudy
of methods in problems of forecasting, the implementation of biometric data
security in telecommunications.
Part III Modern Challenges in RadioElectronics Technologies contains
actual papers, which show some effective technological solutions that can be used
for the implementation of novel systems.
For the convenience of the readers, we briefly summarize contents of the
chapters accepted.
v
vi Preface
Part I Modern Challenges in Information Technologies.
The first chapter presented by M. Ilchenko, L. Uryvsky, S. Osypchuk The Main
Directions of Improving Information and Communication Technologies in the
Global Trends introduces an analysis of modern and promising directions offor-
mation, processing and transmission of information. Information and telecommu-
nication technologies (ITT) in the light of global trends are considered as a single
technologicalcomplex.KeytrendsinthedevelopmentofITTidentified,including,
in the light of the new breakthrough achievements of 2019, which are associated
withthefurtherdevelopmentofITT.Particularaccentisattachtothedevelopment
of mobile telecommunications (technology 5G and 6G), the development of IoT,
the penetration of ITT into the development of Industry 4.0, and the integration
oftheglobalsatelliteInternet.TheactivedesireofUkraineinthestructureofITTto
be at the level of world modern trends is emphasized.
The chapter From Big Data to Smart Data: the most effective Approaches for
Data Analytics by A. Luntovskyy, L. Globa, B. Shubyn focuses on the problem
of thick and server-less mobile applications (Cyber-PHY, IoT, sensor networks,
robotics), real-time network applications (thin clouds clients), that can generate
large arrays of unmanaged, weakly structured, and non-configured data of various
types, known as “big data.” With the acceleration of industrial development
“Industry 4.0” processing of such data became considerably more complicated.
However,theso-calledproblem“bigdata”ishardtosolveorresistnowadays.The
paper discusses the best practises and case studies for data analytics aimed to
overcomingofthebigdata problematics under a slogan: “FromBigData toSmart
Data!”
The chapter Cloud-Based Architecture Development to share Vehicle and
TrafficInformationforIndustry4.0byIbrahimSerhatBulut,HaciIlhancovers
the automotive and technology sectors that have developed very rapidly over the
past decade. In addition to this growth, it also introduced the term Industry 4.0,
which is used to represent the current Industrial Revolution. This revolution
encompasses many sectors from manufacturing to health care. With Industry 4.0,
digital transformation can create value throughout the entire product lifecycle,
support customer feedback, and provide advanced solutions to the problems to be
experienced. Automatic communication between the vehicle and the management
office will facilitate our lives by enabling different analysis of vehicles such as the
driver’s vehicle usage history, fuel consumption, maintenance indicators, and
determination of a behavioral model with data like temperature. This provides
analysis of the car, the driver’s experience, and the road, preventing critical
problemsandunwantedbehavior,andincreasingsafetyontheroads.Forexample,
during the winter season, municipal employees will not have to wait at night to
interveneinroadfreezing.Employeeswillinstantlymonitorwhichroadsareatrisk
of icing through the data collected from the vehicles on the road and municipal
workerswillsalinizetheminnotime.Thisarticleaimstoimplementaplatformthat
collects and analyzes vehicle sensor data and provides individual and corporate
feedback.UsingtheOBD-IIscanner,itisintendedtohelppreventproblems,reduce
Preface vii
accident rates, and manage different types of vehicles. A ready OBD-II (On Board
Diagnostic)reader device,sup-ported byaBluetooth connection,isusedtocollect
data directly from the Engine Control Unit (ECU) in real-time, using an android-
basedsmartphoneasacloudnetworkconnection.Thearchitecturalstructureinthe
cloud is capable of collecting and analyzing raw data to detect the occurrence of
errors in vehicles. While providing feedback to the user, a smart cloud-based
architecture provides the necessary information to the relevant municipal, fire or
ambulance units by foreseeing traffic accidents, the icing on roads in winter or
asphalt melting in summer. Experiments and tests conducted in Istanbul’s traffic
show that the proposed platform has applicability and potential to use.
In the chapter IoT Cryptanalysis using Neural Cryptography and Post-
Quantum Cryptography by L. Mirtskhulava, N. Gulua, L. Globa, N.
Meshveliani,theauthorsinvestigatedthefeaturesIoTasapowerfultooltocapture
data and analyze them from connected devices capable optimizing the processes
that improves customer service but exposes to security vulnerabilities. IoT spans
personal and sensitive information of the users and many aspects of private life
ofthepersonsandthereforeIoTneedstobeprotect.AssessingIoTsecurity,wecan
evaluatetheecosystemsofIoTamongbillionsofthedevicesconnectedthroughthe
Internet prominent in security analysis of the devices. In IoT security, both the
network security and the devices security are so vital.
Analysis of IoT security using probabilistic NTRU cryptosystem and using
artificial neural network algorithms in cryptanalysis and data encryption is intro-
duce. The authors present two approaches that can withstand communication
attacks. Both cryptography technologies like neural cryptography and post-quan-
tum cryptography are the best solutions we’re using in the given paper. Using
NTRU, we implement the NTRUEncrypt public key encryption algorithm capable
of standing against the attacks from the quantum computers. NTRU allows long-
term cryptanalysis and is significantly faster than the other public-key cryptosys-
tems such as RSA or ECC. The other hand, it is well known that artificial neural
networks are able to explore the solution in the field of cryptanalysis capable to
attackcipheringalgorithmswhereanyofthefunctionscanbeproducedbyaneural
network. Therefore, learning ability of neural networks is used in public-key
cryptography.
In result, using NTRU, it made possible to change keys in a few seconds that
making difficult for an attacker to crack the encryption scheme. Collected dataset
was used to train neural networks. ML classifier has achieved an accuracy of
99.9%. Unsupervised DL algorithms were proposed for detecting attacks in IoT.
NTRU was offered by evaluation of other asymmetric algorithms such as RSA,
ECC.Proposedcryptosystemsarethebettersolutioninencryption,decryption,and
key generation. NTRU does not suffer with factorization. So, asymmetric key
protocolwithlightweightasNTRUisbettersolutionforsecuringIoTnetwork.In
theotherhand,neuralcryptographygaveanopportunitytouseneuralkeyexchange
protocol that makes faster key exchange schemes. Unsupervised deep learning
algorithms can faster detect attacks in IoT networks.
viii Preface
In Biometric Cryptosystems: Overview, State-of-the-Art and Perspective
Directions by M. Lutsenko, A. Kuznetsov, A. Kiian, O. Smirnov, T.
Kuznetsova,theauthorspresentmoderncryptographicsystemsthatareconstantly
evolvingandimproving.Thisisduetothedevelopmentofnewcomputingsystems
and advanced cryptographic analysis methods, as well as increasing requirements
for speed, security and reliability of used tools. In particular, it was announced an
adventofuniversalquantumcomputers,whichwillbeabletoprovidecryptanalysis
with advanced calculation methods based on fundamentally new physical princi-
ples. The possible use of such devices encourages the development, research, and
standardization of algorithms for post-quantum cryptographic information protec-
tion. Another factor for the development of advanced cryptographic systems is the
biometric technologies popularization. In this work, a critical review and analysis
of the current application of biometric technologies in cryptographic systems is
conducted. In particular, biometric cryptographic systems, which are designed to
generate secure pseudorandom sequences that can be used as cryptographic keys,
passwords etc., are investigated. A comparative analysis of various biometric
cryptosystems with the determination of their advantages and disadvantages is
carried out. The perspective directions for further research are substantiated. Also,
this work presents a new key generation scheme which uses fuzzy extractors from
the biometric data of iris. The proposed method is based on the code-based public
keycryptosystemswhichareconsideredtoberesistanttoquantumcryptanalysis.A
software implementation of this method with experimental studies of the key
generation algorithm and recommendations on the practical application are
proposed.
A.Kuznetsov,I.Oleshko,K.Chernov,M.Bagmut,T.Smirnova(Biometric
Authentication Using Convolutional Neural Networks) discuss an approach to
analysis of biometric identity authentication technologies that are widespread.
Thesesystemsareimplementednotonlyinenterprises,controlled-accessfacilities,
butalso on smartphones ofordinaryusers and inonlineapplications. The problem
ofchoosingoneoftheauthenticationmethodsremainsurgent.Thispaperprovides
a comparative analysis of existing systems and concludes that one of the most
commonandpersistentmethodsisfacialauthenticationsystem.Themostpowerful
types of attacks on the biometric system are attacks on the database of biometric
templatesandattacksonsensorsforobtainingbiometriccharacteristics.Attackson
biometric sensors or spoofing attack are aimed at impersonating another person
throughfake biometric data. The paper deals with thepossibility of special attacks
on the biometric system of authentication by face image. A new method of
detecting fake attacks (spoofing attacks) is proposed. The method is based on the
useofanartificialconvolutionalneuralnetwork,whichwastrainedusingaReplay-
Attack Database from Idiap Research Institute. The obtained results show high
efficiencyoftheproposedmethodofdetectingspoofingattacks:theprobabilitythat
an attack will be detected is 94.98%.
The chapter Transdisciplinary Fundamentals of Information-Analytical
Activity by S. Dovgyi, O. Stryzhak focuses on the problem of accumulation of
large volumes of scientific and technical products (STP), which is a passive
Preface ix
distributed system of knowledge. This research considers transdisciplinary of such
informationresourcesasametacategorythattakesintoaccountthehyperproperties
of big data (big data), namely: a) reflection which implements the principles of
integration, the consistency and the their behavior integrity and guarantee; b)
recursion which implements the recurrence category of their operational transfor-
mation forms during activation; c) reduction on the basis of which these forms
decomposition principle is realized. Their interpretation in the case of big data
processing is implemented in the following areas: i) the information resources
structuralanalysis;ii)formsofinteractionwithinformationresources;iii)definition
of the mechanisms for identifying criteria for selecting appropriate contexts that
neededfortheexpertanalysis.Theactualityofthesuchproceduresimplementation
is based on the need to create the conditions for supporting the effective a large
numberofdiverseinformationarraysprocessingfortheinformationandanalytical
activities of experts. This understanding for solving the Big Data processing
problem is supported by implementation of component architecture of the services
to support the analytical processes of the experts from various thematic sphere of
activity.
In Ontological Fundamentals of Scientific and Education Portals by S.
Dovgyi, N. Gayevska, O. Lisovyi, Iu. Mosenkis, the authors present the
methodology and technological solutions for design and creation of web-based
scientific and educational portals of ontological engineering. Web portals are
defined as network systems of aggregated representation of subject systems of
knowledge. A narrative category is entered, as an integrated representation of
descriptions of passive knowledge systems. All stages of implementation are
considered—theanalysisofsubjectareas,bycontentofwhichcreatesalltheportal
system components,designthestructure andfunctionalon thebasis ofontological
modeling of subject areas, highlighting cross-curricular relationships to determine
conditions of transition in the portal information environment from one state to
another. Mechanisms of dynamic cataloging of information resources of scientific-
educational portal, cluster formation by thematic search profiles for relevant
information are presented. The model of aggregate displaying portal thematic
resourcesisgiven.Formationmeansintheuseofscientificandeducationalportals
on the base of the component architecture of WEB-semantics services are deter-
mined and it describes their mechanisms application with the support of research
and educational-cognitive activity of portal users. Based on the variety of
descriptions of creative activity of Taras Shevchenko, examples of reflection his
legacyintheinformationenvironmentofthescientific-educationalportalaregiven.
Ontological means of dialogue with the image of the writer on the basis of
establishing intertextual links with his works are presented.
Part II Modern Challenges in Telecommunication Technologies.
K. Karpov, D. Syzov, V. Kirova, N. Mareev, E. Siemens (Data Transmission
Performance Enhancement in Multi-gigabit Wide Area Networks) present the
scientific and technical principles of growing information volumes while meeting
therequirementsfortheirquality.Overthepastfewyears,amountofproduceddata
