With the intensification of digitalization of all processes and activities, the issue of information protection and increasing the level of cyber security is becoming important. Particular attention in this aspect should be focused on the field of queuing. The article provides a brief overview of digital transformation and data protection, which shows that the largest share is occupied by accidents of server equipment, infrastructure / network equipment, applications, data storage system equipment and cyber attacks. The authors focus on key aspects and trends related to the cyber threat landscape; argued the need to introduce new tools for biometric identification and authentication, the most promising of which is behavioral biometrics. The proposed comparative characteristic of types of behavioral biometrics allowed to define spheres of their application and to reveal the drawbacks and advantages. Cybers security, cyber attack, cyber threats, identification, authentication, digitalization, The last two years have been significant for the whole world in the paradigm shift of public communications, which has led to the intensification of their digitalization. Despite the fact that traffic in certain industries and activities has decreased, the number of fraudsters remains the same or even increases. This makes the security situation much more complex and dynamic, as new threats become much larger than before. There is a need to develop new approaches to effective technical solutions and take into account the problem of cyber security. In addition, the global COVID-19 pandemic and the resulting quarantine restrictions have changed the global communication landscape and approaches to the use of digital services. Businesses and consumers around the world are forced to respond quickly to changing realities.
2. Digital Transformation and Data Protection 2.1.
2022 Copyright for this paper by its authors.
For industrial organizations, the number of attacks by extortionist programs increased by 500% in
the period from 2018 to 2021, and another 116% - only in the period from January to May 2021 [
A total of 20120074547 records were broken. In early 2021, Veeam conducted extensive research on data protection. Based on the results, the Veeam Data Protection Report-2021 was written (Table 1). The data show that the largest share is occupied by accidents of server equipment, infrastructure / network equipment, applications, storage system equipment and cyber attacks. According to Forbes, in 2020, 1120 leaks and cyber attacks were recorded. Most of these incidents have been reported by the world's leading media.
Cyber Threats During the COVID-19 Pandemic
Countries, organizations and citizens have been greatly affected by the COVID-19 pandemic, which
has changed the conditions of activity, the activity itself and even life as a whole. Note that most cyber
attacks are usually not publicized due to reputational risks, and therefore it is extremely difficult to
calculate the exact number of threats, even for organizations involved in investigating incidents and
analyzing the actions of hacker groups. Most of these studies aim to draw the attention of organizations
and ordinary citizens who are interested in the current state of information security, to the most relevant
methods and motives of cyber attacks as well as to identify major trends in the change of the landscape
of cyber threats [
Let’s highlight key aspects and trends related to the cyber threat landscape [
Organized crime groups are taking advantage of the situation, uncertainty and doubts caused by
COVID-19 and inventing new ways to pose threats to IT and cyber security. In turn, businesses and
people want to have more information and support and be protected. Consumers want more control
over personal information and guarantees about its security in terms of content and secrecy from third
parties [
In these conditions the use of biometrics as an effective means of confirming the correctness of
identification is important in solving queuing problems. It is quite attractive for an organization to
control any access, as biometrics provides a high level of authentication and can be integrated into any
access control system with different keys and passwords [
Threats to biometric systems can occur in the form of fictitious data transmission, when an attempt is made to undermine the principles of system security by providing natural biometric characteristics or artifacts that contain copied or forged characteristics in the middle.
Control access systems can be divided into three classes according to what a person has to present: what he or she knows; what he or she owns; what is part of himself/ herself.
Biometrics uses scientifically justified methods to describe and measure the characteristics of the
body of living beings [
Biometric identification is often called real authentication because it is based on a person's personal characteristics, not on virtual keys or passwords. A feature of biometric identification is the large size of biometric databases: each of the samples is compared with all available records in the database. For use in real life, such a system requires a high speed comparison of biometric characteristics.
Two methods of authentication are used in biometrics: 1. Verification: measurement data are compared with one record offered by an external identifier (nickname, password or other identifier) from the database of registered users; 2. Identification: the measurement data is compared with all entries in the database of registered users, and not only with one of them, selected on the basis of the identifier.
The main purpose of biometrics is to create a registration system that rarely denies access to legitimate users and at the same time completely eliminates the possibility of authorization of attackers. 3.2.
Features of Application of Behavioral Biometrics
Modern authentication technology is behavioral biometrics, which involves the collection of a
variety of data [
Behavioral biometrics can be adapted to a variety of devices, including smart phone operating systems as a whole, not just applications. Each person has unique features of interaction with their digital devices: the speed of typing on the keyboard, the force of pressing or the angle at which the fingers move across the screen. It is almost impossible to reproduce such behavior by any another person.
While behavioral biometrics is most commonly used by banks and financial institutions today, experts are expected to use it in e-commerce, online services, healthcare, government and in many more spheres in the near future [15].
Of course, as in any promising technology, there are pros and cons. Among the first are: inaccuracies in identification due to the fact that user behavior is not always constant, which is associated with, for example, fatigue, intoxication, malaise or haste, as well as the availability of many personal data to determine standard behavior of a user. The positive features include the fact that each user has their own unique set of behavioral characteristics that are analyzed; to perform the identification does not require a change in the script intended for the user: the method of seamless integration; increased recognition accuracy in multifactor identification systems [16].
There are several methods of behavioral biometrics [17]. Their comparative characteristics are presented in Table 2.
average
impossible to forge;
d in
High error rate until the user gets used to the notebook for compare and check patterns. A high-quality tablet can capture behavioral characteristic s such as speed, pressure, and time spent signing. At the registration stage, a person must sign up several times on a tablet to collect data.
Then, signature recognition algorithms extract unique characteristic s such as
time, pressure,
speed, direction of impact, important points on the signature path, and signature size.
assigns different degrees of importance to these points
say the word or phrase into the microphone.
This is necessary to obtain a sample of
human language. The electrical signal of the
recognition time; contactless scanning Sensitivity of technology to quality of a microphone and noise;
risk of counterfeitin g
Voice recognitio n microphone will be converted to digital using an analog-todigital converter. It is written to computer memory in the form of a digitized sample. The computer
then compares and tries to compare the voice of the person speaking with the stored digitized sample and identifies the person.
Speaker recognition focuses on the context of the phrase said by the user, not on the recognition of his voice
Voice recognition function compares a spoken phrase to a
digital pattern. It is used as a means of identification and authenticatio n in security systems such as access control and timekeeping.
s, Google LLC,
Online banking sector, emergency services, call center recognition, high demand for voice recognition in healthcare
recognition
time; contactless scanning.
.
Risk of counterfeitin g; inability to reduce external noise; problems
with recognition accuracy Recognitio n on the go templates with a very
high probability of correct interpretation . Each person's voice includes physiological and behavioral characteristic s.
Physiological aspects depend on the size and shape of the mouth, throat, larynx, nasal cavity, body weight and other factors.
Behavioral traits depend on language, level of education and place of residence, which can lead to certain intonations, accents and dialects
Stroke biometrics captures step patterns using video and then converts the mapped data into a mathematical equation. This type of biometrics is invisible, making it ideal for mass crowd monitoring.
Contactless scanning; possibility to cover a large area; fast recognition time.
is evolving rapidly
Not as reliable as
other biometric methods; clothing and footwear can affect the accuracy of recognition
Contactless scanning;
fast recognition
time; increases
the accuracy of recognition
in combinatio
n with other forms
of biometrics
The technology is being refined
Biometric data can be stored on different media depending on the type and specific biometric technology. Data can be stored on a biometric database server as part of public infrastructure or can be physically distributed to private companies. Biometric data can also be stored on smart phones that use fingerprint and face recognition technology.
None of the above personal characteristics of an individual can be compared in reliability of recognition with the genetic code of a person. However, practical methods of identification that use the unique features of fragments of the genetic code are currently rarely used due to their complexity and high cost.
Thus, the identification of the individual as the consumer of information is becoming increasingly important. It explains the huge interest in biometric technologies and the role of information, and hence its protection from unauthorized access. They are quite attractive for the organization in charge of access, as they provide a high level of authentication, can be integrated into any access control system simultaneously with different keys and passwords. 5. References [15] F. Bahmaninezhad; C. Zhang; J.H. Hansen. Convolutional Neural Network Based Speaker DeIdentification. Odyssey, 2018, 255–260. https://www.semanticscholar.org/paper/ConvolutionalNeural-Network-Based-SpeakerBahmaninezhad
Zhang/f2cd2f81b188166058ea04b454a4c59135d744a5 [16] Y.R. Vampolskiy, V. Govindaraju. Behavioural biometrics: a survey and classification, Int. J.
Biometrics, 2008, Vol. 1, No. 1, 81–113. [17] A.K. Anil, K. Jain, Biometrics of Next Generation—An Overview. http://biometrics.cse.msu.edu/ Publications/GeneralBiometrics/JainKumarNextGenBiometrics_BookChap10.pdf