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Industrial Internet of Things (IIoT) and Industry 4.0 empower interrelation among manufacturing processes, industrial machines, and utility services. The time-critical data collected from heterogeneous sensing devices are usually communicated to processing points for analysis and aggregation as the basis of IIoT. The IIoTs’ service quality typically depends on data integrity and accuracy, which could be exploited by injecting malicious events such as false data injection and data poisoning attacks. Thus, effective anomaly recognition and explanation are critical for ensuring quality services and empowering security administrators to interpret the causal reasoning of prediction decisions and underlying data evidence. This study proposes an autoencoder-based detection framework using convolutional and recurrent networks to discover cyber threats in IIoT networks and explain the model. A two-step Sliding Window (SW) is applied to learn the latent representations of data features better. Malicious points from the raw time series are transformed into fixed-length series through the first-step SW. Every series is converted into continuous time-reliant subseries via another smaller SW to learn latent representations of malicious events. Fully connected networks use the extracted temporal and spatial features for the classification and explanation of attack events. The empirical results revealed that this framework effectively extracts features that include contexts of malicious patterns. This demonstrated that the proposed framework is robust in detecting malicious events using multiple evaluation metrics and outperforming the contemporary state-of-the-art methods, indicating its suitability as an operative application method in real-world IIoT-based networks.

As regulatory bodies require full implementation of security controls in nuclear power plants (NPPs), security functions for critical digital assets are currently being developed. For the ultimate introduction of security controls, not alternative measures, it is important to understand the relationship between possible cyber threats to NPPs and security controls to prevent them. To address the effectiveness of the security control implementation, this study investigated the types of cyber threats that can be prevented when the security controls are implemented through the mapping of the reorganized security controls in RS-015 to cyber threats on NPPs. Through this work, the cyber threat that each security control can prevent was confirmed, and the effectiveness of several strategies for implementing the security controls were compared. This study will be a useful reference for utilities or researchers who cannot use design basis threat (DBT) directly and be helpful when introducing security controls to NPPs that do not have actual security functions.

Cloud computing is now being utilized as a prospective alternative for catering storage service. Security issues of cloud storage are a potential deterrent in its widespread adoption. Privacy breach, malicious modification and data loss are emerging cyber threats against cloud storage. Recently, a fog server based three-layer architecture has been presented for secure storage employing multiple clouds. The underlying techniques used are Hash-Solomon code and customized hash algorithm in order to attain the goal. However, it resulted in loss of smaller portion of data to cloud servers and failed to provide better modification detection and data recoverability. This paper proposes a novel fog-centric secure cloud storage scheme to protect data against unauthorized access, modification, and destruction. To prevent illegitimate access, the proposed scheme employs a new technique Xor-Combination to conceal data. Moreover, Block-Management outsources the outcomes of Xor-Combination to prevent malicious retrieval and to ensure better recoverability in case of data loss. Simultaneously, we propose a technique based on hash algorithm in order to facilitate modification detection with higher probability. We demonstrate robustness of the proposed scheme through security analysis. Experimental results validate performance supremacy of the proposed scheme compared to contemporary solutions in terms of data processing time.

This chapter discusses the importance of Machine Learning and Deep Learning, two methodologies which have gained importance due to the impact of Digital Transformation and the increasing growth of data sets to Big Data generated through the Internet connectivity. Machine Learning is a subset of Artificial Intelligence used to create algorithms which can modify itself without human intervention to generate a desired output. Deep Learning is also a sub-set of Artificial Intelligence used to create algorithms and functions similar to those in Machine Learning, but there are numerous layers of these algorithms which provide different interpretation to the data it feeds on. Machine Learning and Deep Learning methods can be used for computer system or network analysis in case of cyber threat intrusion incidents detection. This is essential to prevent intrusion of malicious code and to enhance cybersecurity.

This article attempts to explain the forms of Indonesian cyber diplomacy related to the protection of the use of information technology. In this case, Indonesia as the fourth largest country in the world often gets cyber threats and attacks. This was then followed up with efforts to protect it domestically, but was constrained by threats from abroad.The research method used in this study uses a qualitative descriptive analytical approach using the theoretical framework of cyber diplomacy and the concept of information and communication technology. The case analysis will explain the causes and effects of holding Indonesian cyber diplomacy based on secondary data. The author finds that the Indonesian government does not only use a legal approach through the ITE Law, but also culture, technological renewal, and diplomacy towards various countries.

Cybersecurity is crucial at present because cyber threats (e.g., phishing) have become a very common occurrence in everyday life. A literature review showed that there are no studies based on cybersecurity awareness which involved a large number of Thai users. Thus, this research focused on the cybersecurity awareness of approximately 20,000 nationwide employees in a large financial institution in Thailand. The study consisted of three phases, a first phishing attack, knowledge transfer through a mixed-approach and a second phishing attack with different content. After data validation and analysis of the results, it was found that the level of cybersecurity awareness of employees improved significantly. The number of employees who opened the phishing email decreased by 71.5%. Therefore, this approach could be applied to cybersecurity enhancement in other organizations and other sectors/industries. Also, it was found that gender played a significant role in cybersecurity awareness within the Thai cybersecurity ecosystem since Thai female employees were found to have a higher level of cybersecurity awareness than male employees. Furthermore, it was found that the different generations of Thai employees (Generations Y and X and Baby Boomers) did not affect cybersecurity awareness.

This paper focuses on understanding the characteristics of multiple types of cyber-attacks through a comprehensive evaluation of case studies of real-world cyber-attacks. For each type of attack, we identify and link the attack type to the characteristics of that attack and the factors leading up to the attack, as observed from the review of case studies for that type of attack. We explored both the quantitative and qualitative characteristics for the types of attacks, including the type of industry, the financial intensity of the attack, non-financial intensity impacts, the number of impacted customers, and the impact on users’ trust and loyalty. In addition, we investigated the key factors leading up to an attack, including the human behavioral aspects; the organizational–cultural factors at play; the security policies adapted; the technology adoption and investment by the business; the training and awareness of all stakeholders, including users, customers and employees; and the investments in cybersecurity. In our study, we also analyzed how these factors are related to each other by evaluating the co-occurrence and linkage of factors to form graphs of connected frequent rules seen across the case studies. This study aims to help organizations take a proactive approach to the study of relevant cyber threats and aims to educate organizations to become more knowledgeable through lessons learned from other organizations experiencing cyber-attacks. Our findings indicate that the human behavioral aspects leading up to attacks are the weakest link in the successful prevention of cyber threats. We focus on human factors and discuss mitigation strategies.

To increase situational awareness, major cybersecurity platforms offer Cyber Threat Intelligence (CTI) about emerging cyber threats, key threat actors, and their modus operandi. However, this intelligence is often reactive, as it analyzes event log files after attacks have already occurred, lacking more active scrutiny of potential threats brewing in cyberspace before an attack has occurred. One intelligence source receiving significant attention is the Dark Web, where significant quantities of malicious hacking tools and other cyber assets are hosted. We present the AZSecure Hacker Assets Portal (HAP). The Dark Web-based HAP collects, analyzes, and reports on the major Dark Web data sources to offer unique perspective of hackers, their cybercriminal assets, and their intentions and motivations, ultimately contributing CTI insights to improve situational awareness. HAP currently supports 200+ users internationally from academic institutions such as UT San Antonio and National Taiwan University, law enforcement entities such as Calgary and Ontario Provincial Police, and industry organizations including General Electric and PayPal.

The paper aims to explore the behavior of Russian school-age children who are faced with a new social and psychological phenomenon: threats associated with the digital environment. Our focus was on the ability (psychological as well as technical) of teenagers to stand against cyber threats. At the preliminary stage of the research we analysed both Russian and international studies on how to promote cyber security awareness among school children and, in particular, how to respond to the cyber threats associated with the new social context formed by the COVID-19 pandemic. We used survey research as the main method and designed a special questionnaire that was then offered to a group of 7—11-grade students (N=5,682) from seven Russian regions in the late 2020. The research data was processed using the SPSS and STATISTICA programmes. The data allowed us to assess the degree in which the children were familiar with the methods and means of protecting sensitive personal information, as well as their ability to stand against cyber threats basing on their knowledge and skills. The research also helped us to identify the role of schools in promoting the children’s readiness for the modern digital reality. The typical shortcomings in the digital competences of school-age children are noteworthy here too, first of all, the ones concerning the knowledge of cyber risk types related to the use of social media and internet communication services. We conclude that there is a need for systemic measures on various levels of education that would help reduce the cyber risks for adolescents on the social media and promote the quality of digital competence development in Russian schools.

Introduction The integration of artificial intelligence (AI) systems into medical imaging is advancing the practice and patient care. It is thought to further revolutionise the entire field in the near future. This study explored Ghanaian radiographers’ perspectives on the integration of AI into medical imaging. Methods A cross‐sectional online survey of registered Ghanaian radiographers was conducted within a 3‐month period (February‐April, 2020). The survey sought information relating to demography, general perspectives on AI and implementation issues. Descriptive and inferential statistics were used for data analyses. Results A response rate of 64.5% (151/234) was achieved. Majority of the respondents (n = 122, 80.8%) agreed that AI technology is the future of medical imaging. A good number of them (n = 131, 87.4%) indicated that AI would have an overall positive impact on medical imaging practice. However, some expressed fears about AI‐related errors (n = 126, 83.4%), while others expressed concerns relating to job security (n = 35, 23.2%). High equipment cost, lack of knowledge and fear of cyber threats were identified as some factors hindering AI implementation in Ghana. Conclusions The radiographers who responded to this survey demonstrated a positive attitude towards the integration of AI into medical imaging. However, there were concerns about AI‐related errors, job displacement and salary reduction which need to be addressed. Lack of knowledge, high equipment cost and cyber threats could impede the implementation of AI in medical imaging in Ghana. These findings are likely comparable to most low resource countries and we suggest more education to promote credibility of AI in practice., This study assessed the perspectives of radiographers on the integration of artificial intelligence (AI) into medical imaging (MI). The radiographers have a positive attitude towards the clinical application of AI in MI. However, some were concerned about AI‐related errors, job displacement and reduction of basic salary, and many perceived that the lack of knowledge, high equipment costs and cyber threat could affect the implementation of AI in MI in Ghana.

Given the prevailing state of cybersecurity, it is reasonable to understand why cybersecurity experts are seriously considering artificial intelligence as a potential field that can aid improvements in conventional cybersecurity techniques. Various progressions in the field of technology have helped to mitigate some of the issues relating to cybersecurity. These advancements can be manifested by Big Data, Blockchain technology, Behavioral Analytics, to name but a few. The paper overviews the effects of applications of these technologies in cybersecurity. The central purpose of the paper is to review the application of AI techniques in analyzing, detecting, and fighting various cyberattacks. The effects of the implementation of conditionally classified “distributed” AI methods and conveniently classified “compact” AI methods on different cyber threats have been reviewed. Furthermore, the future scope and challenges of using such techniques in cybersecurity, are discussed. Finally, conclusions have been drawn in terms of evaluating the employment of different AI advancements in improving cybersecurity.

The paper describes cyber threats to the security of critical infrastructures with an emphasis on SCADA systems. In addition to the theoretical founda­tions of the work, an application containing a SIEM software solution has been implemented.

Cyber threats in the context of the spread of modern challenges are outlined. The мeasures to strengthen the capacity of the national cybersecurity system are regulated. The priority principles of institutional and functional support for the development of the national cybersecurity system are detailed. The measures taken to institutionally strengthen security in cyberspace in some foreign countries are analyzed. The principles of forming the vertical of control and coordination of measures in the field of cybersecurity are highlighted. The powers of the National Coordination Center for Cyber Security as a working body of the National Security and Defense Council of Ukraine are outlined. The capacities of some actors in the national cybersecurity system have been clarified in order to avoid duplication. The directions of improvements of the priority principles of institutional and functional support of cybersecurity based on the threatening trends of today have been identified.

This paper reports an analysis of the software (SW) safety testing techniques, as well as the models and methods for identifying vulnerabilities. An issue has been revealed related to the reasoned selection of modeling approaches at different stages of the software safety testing process and the identification of its vulnerabilities, which reduces the accuracy of the modeling results obtained. Two steps in the process of identifying software vulnerabilities have been identified. A mathematical model has been built for the process of preparing security testing, which differs from the known ones by a theoretically sound choice of the moment-generating functions when describing transitions from state to state. In addition, the mathematical model takes into consideration the capabilities and risks of the source code verification phase for cryptographic and other ways to protect data. These features generally improve the accuracy of modeling results and reduce input uncertainty in the second phase of software safety testing. An advanced security compliance algorithm has been developed, with a distinctive feature of the selection of laws and distribution parameters that describe individual state-to-state transitions for individual branches of Graphical Evaluation and Review Technique networks (GERT-networks). A GERT-network has been developed to prepare for security testing. A GERT-network for the process of checking the source code for cryptographic and other data protection methods has been developed. A graphic-analytical GERT model for the first phase of software safety testing has been developed. The expressions reported in this paper could be used to devise preliminary recommendations and possible ways to improve the effectiveness of software safety testing algorithms

Modern artificial intelligence based medical imaging tools are vulnerable to model fooling attacks. Automated medical imaging methods are used for supporting the decision making by classifying samples as regular or as having characters of abnormality. One use of such technology is the analysis of whole-slide image tissue samples. Consequently, attacks against artificial intelligence based medical imaging methods may diminish the credibility of modern diagnosis methods and, at worst, may lead to misdiagnosis with improper treatment. This study demonstrates an advanced color-optimized one-pixel attack against medical imaging. A state-of-the-art one-pixel modification is constructed with minimal effect on the pixel's color value. This multi-objective approach mitigates the unnatural coloring of raw none-pixel attacks. Accordingly, it is infeasible or at least cumbersome for a human to see the modification in the image under analysis. This color-optimized one-pixel attack poses an advanced cyber threat against modern medical imaging and shows the importance of data integrity with image analysis.

The aim of this paper is show how existing legal frameworks applied to civil aviation might be relevant in the context of cyberspace. Security threats to civil aviation operations have become more sophisticated and challenging to deal with. One that is emerging, and arguably even more complicated and sophisticated to manage, is the cyber-attack. This article is interdisciplinary as it briefly defines cyber-attack and describes the nature of the threat it poses to aviation and society generally, but also focuses on the international legal instruments that are available to address cyberterrorism and reflects on the challenges faced by aviation through cyberspace. Conclusions offer some food for thought on the article’s conclusions and on possible developments in the relationship between civil aviation and cyber security.

Cyber Threat Intelligence (CTI) is the emerging strategy of cyber defense which helps organizations to combat the latest and more sophisticated cyber threats. Gathering this threat information, analyzing and communicating it between the security teams is very difficult and challenging because of the heterogeneous aspects involved. The necessity of sharing the intelligence related data collected by organizations is increasing day by day to counter the ever changing and highly dynamic threat landscape. In this paper an attempt is made to understand CTI concept and how it is collected and analyzed to form useful actionable intelligence are observed. The importance of Threat intelligence sharing, and various standards working in the area of TIS are also mentioned. Finally the primary challenges in TIS are given a light in a broad view

Information technology (IT) is the key component of e-government infrastructures, but at the same time, it makes governments more exposed to the cyber risk. In this study, we take an empirical approach to investigate the cyber risk in the public sector. We describe the most common cyber threats facing local governments and build linear models to explain the relationships between cyber losses, local government budgets, and IT expenditures. We find that local governments are affected by cyber incidents more frequently, and disruption incidents that lead to the malfunction of e-government services are on the rise. In addition, the magnitude of cyber losses used to have a strong positive relationship with the affected governments’ budget size. However, in recent years, this relationship is weakening, and small local governments are more heavily impacted by cyber incidents than before. Our findings further suggest that investing in information technology is becoming more effective in terms of lowering the loss-to-budget ratio. However, this also means local governments with small budgets do not benefit from this change as much as the large ones do.

The article examines the current state of cybersecurity and identification of cyber threats in the use of credentials, the formulation of measures to minimize the risk of theft, damage or loss of confidential accounting information in the cyber environment of its use and maintenance

The business world has been significantly affected by network intrusion leading to infringement of privacy and unprecedented economic losses. Therefore, real-time monitoring of network devices is important due to the enhanced and complex network systems in organizations and associated cyber threats. Real-time monitoring provides adequate alerts and updates regarding specific networks and their performance as soon as they occur. Constant monitoring of devices also makes it possible for organizations to detect any possible challenges that the networks may be encountering. This paper examines the effectiveness of real-time monitoring of network devices in a bid to enhance network security. The study was an empirical review of recently published research papers, journals, internet sites, and books with relevant content. The findings of this study revealed that Real-time device monitoring has many potential advantages to organizations by securing their systems thereby enhancing their overall performance.

The aim of the study is twofold. Firstly, it is believed to be the first study of its kind to explore the interconnectivity of the current stage of the EU’s Digital Single Market (DSM)3 (European Commission, 2015c) and its development prospects within the framework of the EU and its Member States’ SD approach. Secondly, it provides further evidence for the policy debate on the essential priorities of DSM deemed to be a stimulus to the future SD of the EU. It is an attempt to fill the existing gap in research conducted so far on SD and its correlation with the building process of the digital market in the EU. The task is to present by using the method of synthesis and deduction, the essence and milieu of the contemporary processes of building the DSM in the EU in the context of its potential influence for the SD of the EU and its Member States. Due to the interdisciplinary and complexity of the data analyses, mixed research methods were used to integrate quantitative and qualitative analyses and results.

The article examines the growing risks and security threats faced by the financial sector. This problem is currently most relevant, as the increased demand for security in the banking sector encourages the development and introduction of new technologies (including machine learning and artificial intelligence), while at the same time creating new vulnerable areas and related problems.

Cyber Threat sharing helps with defending against cyber attacks in a timely manner. Many frameworks have been proposed for CTI sharing such as Structured Threat Information Expression (STIX) and Trusted Automated Exchange of Intelligence Information (TAXII). However, CTI sharing in a controlled and automated manner is critical. In this paper, we demonstrate Relationship Based Access Control (ReBAC) as an appropriate model for CTI sharing. We also develop an approach for automated threat detection, generation and sharing of structured CTI and taking course of actions to mitigate cyber threats. Finally, we implement an Automated Cyber Defense System in a cloud based environment.

The relevance of the problem of the banking sector development lies in the fact that banks, implementing their economic policy, can ensure continuous sustainable growth of the entire national economy. The study aims to offer long-term proposals for the development of the banking sector of Azerbaijan, which will bring it to the next level. During the research the author used such methods as the study of literary sources, analysis, synthesis, abstraction and special methods. The study presents six major macroeconomic factors that significantly affect the rate of the long-term growth of the banking sector: customer focus, legal framework, new banking technologies, cyber threats, use of the experience of large IT companies, and qualified personnel. The author analyzed the effects of these factors on the long-term growth rate. Recommendations are given on the use of innovation and advanced technologies for the benefit of development, that will allow building an efficient and competitive banking system. Based on the results of the study, the author formulated proposals for improving the banking sector of Azerbaijan that will bring it to the next level. In particular, it is proposed to optimize robotic process automation, namely, to completely revise the existing methods of work, and not just solve problems using robotization. The author concluded that there is a long way ahead towards ensuring the sustainable development of the banking sector in Azerbaijan, which is currently at the beginning of its journey. Further research on this topic will allow a deeper study of digital opportunities and prospects for the integrated implementation of innovation.

Many healthcare organizations are exposed to various cyber threats The increase in the frequency of these cyber threats can also be observed during the Covid-19 pandemic The security of information systems in hospitals and their management is also not part of the management of facilities in these organizations The paper presents the possibilities of securing facility management processes in healthcare organizations from a security point of view There is an analysis of security aspects of a particular medical facility and its information system with emphasis on the application of regular facility management Analysis and evaluation of tools for ensuring the security of the hospital information network is also applied The contribution of the paper is the identification and expression of the correlation between cyber threats and the following modules of the information system in the medical facility Another part of the proven research compares safety mechanisms and their possible failure in a selected hospital The main research results, which are based on the evaluation of safety aspects in these organizations, can be further used as a platform for the effectiveness of processes in healthcare and thus increase synergies between safety levels and ensure facility management processes © 2021, World Scientific and Engineering Academy and Society All rights reserved

Демчишак Н.Б., Шкиря А.С. УПРАВЛІННЯ РИЗИКАМИ У ФІНАНСОВОМУ СЕКТОРІ УКРАЇНИ В УМОВАХ КІБЕРЗАГРОЗ І ПОСТПАНДЕМІЧНОГО ВІДНОВЛЕННЯ ЕКОНОМІКИ Мета. Обґрунтування підходів вітчизняних та зарубіжних вчених до управління ризиками у фінансовому секторі України в умовах кіберзагроз та необхідності забезпечення національної безпеки і постпандемічного відновлення економіки. Методика дослідження. У статті використано загальнонаукові та спеціальні методи наукових пошуків, зокрема: індукції, дедукції, наукового абстрагування – для розкриття суті понять «кіберзагроза», «кібербезпека» та «діджиталізація»; статистичний і графічний методи – для оцінки поточної ситуації в сфері кіберзахисту у світі та національного індексу кібербезпеки; методи аналізу і синтезу – при обгрунтуванні висновків за результатами дослідження. Результати дослідження. Розглянуто дефініції кіберризику, підходи до їх тлумачення та класифікацію. Аргументовано важливість забезпечення кібербезпеки в умовах цифровізації національної економіки. Проаналізовано положення Стратегії розвитку фінансового сектору України до 2025 року. Досліджено світову статистику частоти та збитків внаслідок здійснення кібератак та ідентифіковано кіберзагрози, які завдали найбільших збитків в Україні. Проведено аналіз позицій України у Національному індексі кібербезпеки 2020. Обгрунтовано напрями запобігання кіберзагрозам, які можуть бути корисними для українських компаній. Наукова новизна результатів дослідження. Запропоновано авторське визначення поняття «кіберризик», у якому акцентується особлива увага на наслідках кіберзагроз. Обґрунтовано важливість управління кіберризиками у умовах невідворотності діджиталізації у фінансовому секторі України. Запропоновано підходи в частині запобігання кібератакам, реалізаціях яких необхідна для успішної цифрової трансформації України. Практична значущість результатів дослідження. Отримані результати дослідження будуть сприяти формуванню ефективної системи управління ризиками у фінансовому секторі України в умовах діджиталізації фінансового простору та постпандемічного відновлення національної економіки. Ключові слова: національна безпека, кіберризик, кіберзагроза, кіберзахист, діджиталізація, постпандемічне відновлення, фінтех. Demchyshak N.B., Shkyria A.S. RISK MANAGEMENT IN THE FINANCIAL SECTOR OF UKRAINE IN THE CONTEXT OF CYBER THREATS AND POST-PANDEMIC ECONOMIC RECOVERY Purpose. The aim of the article is substantiation of approaches of domestic and foreign scientists to risk management in the financial sector of Ukraine in the context of cyber threats and the need to ensure national security and post-pandemic economic recovery. Methodology of research. General scientific and special methods of scientific research are used in the article, in particular: induction, deduction, scientific abstraction - to reveal the essence of the concepts of "cyber threat", “cyber security" and "digitalization"; statistical and graphical methods - to assess the current situation in the field of cyber defence in the world and the national cyber security index; methods of analysis and synthesis - in substantiating the conclusions of the research. Finding. Definitions of cyber risk, approaches to its interpretation and classification were considered. The importance of cyber security in the digitalization of the national economy was argued. The Strategy of Ukrainian Financial Sector Development until 2025 is analysed. The world statistics of frequency and losses due to cyber-attacks are studied and the cyber threats that caused the greatest losses in Ukraine are identified. The analysis of Ukraine’s positions in the National Cyber Security Index 2020 is carried out. The directions of cyber threat prevention that can be useful for Ukrainian companies are substantiated. Originality. The author’s definition of the term "cyber risk" is proposed, in which special attention in focused on the effects of cyber threats. The importance of cyber risk management in the conditions of inevitability of digitalization in the financial sector of Ukraine is substantiated. Approaches to the prevention of cyber-attacks, the implementation of which is necessary for the successful digital transformation of Ukraine, are proposed. Practical value. The results of the research will contribute to the formation of an effective risk management system in the financial sector of Ukraine in terms of digitalization of the financial space and post-pandemic recovery of the national economy. Key words: national security, cyber risk, cyber threat, cyber defence, digitalization, post-pandemic recovery, fintech.

Smart cities and their applications have become attractive research fields birthing numerous technologies. Fifth generation (5G) networks are important components of smart cities, where intelligent access control is deployed for identity authentication, online banking, and cyber security. To assure secure transactions and to protect user’s identities against cybersecurity threats, strong authentication techniques should be used. The prevalence of biometrics, such as fingerprints, in authentication and identification makes the need to safeguard them important across different areas of smart applications. Our study presents a system to detect alterations to biometric modalities to discriminate pristine, adulterated, and fake biometrics in 5G-based smart cities. Specifically, we use deep learning models based on convolutional neural networks (CNN) and a hybrid model that combines CNN with convolutional long-short term memory (ConvLSTM) to compute a three-tier probability that a biometric has been tempered. Simulation-based experiments indicate that the alteration detection accuracy matches those recorded in advanced methods with superior performance in terms of detecting central rotation alteration to fingerprints. This makes the proposed system a veritable solution for different biometric authentication applications in secure smart cities.

Ревак І.О., Грень Р.Т. ОСОБЛИВОСТІ ФОРМУВАННЯ БЕЗПЕЧНОГО КІБЕРПРОСТОРУ В УМОВАХ РОЗВИТКУ ЦИФРОВОЇ ЕКОНОМІКИ Мета. Розкриття особливостей формування безпечного кіберпростору в умовах розвитку цифрової економіки, обґрунтування напрямів діяльності правоохоронних органів щодо запобігання кіберзлочинності. Методика дослідження. Теоретичним підґрунтям дослідження стали фундаментальні положення сучасної економічної теорії, наукові праці вчених, нормативні та законодавчі акти України з питань кібербезпеки та розвитку цифрової економіки. Для досягнення поставленої мети використовувалися такі загальнонаукові та спеціальні методи: абстрактно-логічний (для обґрунтування ключових характеристик інформаційного простору в умовах зростання цифровізації економіки), системний (для розгляду взаємозв’язків між різними структурними підрозділами та суб’єктами бізнесу щодо розробки заходів з протидії транснаціональній злочинності), індуктивної логіки (при дослідженні напрямів діяльності правоохоронних органів щодо недопущення реальних та потенційних кіберзлочинів), дедуктивний (для визначення ефективних засобів контролю безпеки при управлінні кіберзагрозами), системно-структурного аналізу (для виявлення та аналізу закономірностей, тенденцій та особливостей розвитку цифрової економіки). Результати дослідження. Досліджено особливості безпечного віртуального середовища в умовах розвитку цифрової економіки, враховуючи специфіку формування інформаційного суспільства та цифровізації економічних відносин, розвиток економічних процесів, зокрема їх входження до міжнародного цифрового ринку. Окреслено проблемні питання забезпечення інформаційної та кібернетичної безпеки. Акцентовано увагу на необхідності розробки та впровадження технологій захисту та протидії кібератакам, управління кіберризиками, оцінювання ефективності засобів контролю безпечного кіберпростору. Проаналізовано ефективні засоби протидії скоєнню злочинів у сфері цифрової економіки, обґрунтовано перспективні напрями забезпечення правопорядку у кіберпросторі. Наукова новизна результатів дослідження. Обґрунтовано теоретико-методичні положення та прикладні рекомендації щодо формування безпечного кіберпростору в умовах розвитку цифрової економіки, створення інституційного підґрунтя для інтеграції державних та бізнес-структур на основі інформаційних технологій. Практична значущість результатів дослідження. Розроблені науково-прикладні рекомендації щодо протидії кіберзлочинам на макро- на мікрорівнях можуть бути використані у роботі правоохоронних органів. Ключові слова: цифрова економіка, цифрові технології, кібербезпека, кіберпростір, кіберзлочинність, кіберзагрози, інформаційно-комунікаційні технології. Revak I.O., Gren R.T. PECULIARITIES OF THE FORMATION OF SECURE CYBERSPACE IN THE DIGITAL ECONOMY Purpose. The aim of the article is to reveal the peculiarities of the formation of secure cyberspace in the digital economy, to substantiate the activities of law enforcement agencies to prevent cybercrime. Methodology of research. The theoretical basis of the study were the fundamental provisions of modern economic theory, scientific works of scientists, regulations and legislation of Ukraine on cyber security and the development of the digital economy. To achieve this goal, the following general and special methods were used: abstract and logical (to substantiate the key characteristics of the information space in the context of growing digital economy), system (to consider the relationship between different departments and businesses to develop measures to combat transnational crime), inductive logic (in the study of law enforcement activities to prevent real and potential cybercrime), deductive (to determine effective means of security control in the management of cyber threats), system and structural analysis (to identify and analyse patterns, trends and features of the digital economy). Findings. The peculiarities of a secure virtual environment in the conditions of digital economy development are studied, taking into account the specifics of information society formation and digitalization of economic relations, development of economic processes, in particular their entry into the international digital market. Problematic issues of information and cyber security are outlined. Emphasis is placed on the development and implementation of technologies to protect and counter cyber-attacks, cyber risk management and evaluation of the effectiveness of safe cyberspace control. Effective means of counteracting the commission of crimes in the digital economy are analysed, perspective directions of ensuring law and order in cyberspace are substantiated. Originality . The scientific novelty lies in the substantiation of theoretical and methodological provisions and applied recommendations for the formation of secure cyberspace in the digital economy, the formation of the institutional basis for the integration of government and business structures based on information technology. Practical value. The practical significance of the obtained results lies in the development of scientific and applied recommendations for combating cybercrime in the work of law enforcement agencies. Key words: digital economy, digital technologies, digitalization, cyber security, cybercrime, cyber threats, cyberspace, information and communication technologies.

Healthcare is one of the most targeted industries by cybercriminals. The healthcare sector is far behind in cybersecurity as compared to other organizations. The vulnerabilities in the system open the door for cybercriminals to exploit it and get unauthorized access into the system or network to do a malicious activity. Healthcare should have to take cyber threats seriously and follow a security framework that detects and mitigates cyber threats. This chapter presents all cyber threat actors that exist in the healthcare sector, common cyber-attacks that can be launched against all actors, and real incidents that took place during the past years. Based on these, the authors propose in a tabular form a set of recommendations that can be used as countermeasures against any type of attack.

Security is paramount in protecting critical infrastructures such as healthcare, power, water distribution, and transport system. Modern critical infrastructures are increasingly turning into distributed, complex Cyber-Physical systems that enable data monitoring in near real-time conditions. With the advancement in distributed IoT systems, the magnitude of the threats has increased. An innovative approach is to adopt Privacy-Preserving machine learning solutions to detect any possible anomalies in such infrastructures. This issue aims to contribute to the body of knowledge on enhancing critical infrastructure security in developing machine learning solutions and benefiting our future fighting against cyber threats in critical infrastructure.

Computing is the foundation of cyberspace, and all activities in cyberspace are built on the basis of computing. At the same time, cyberspace and its underlying infrastructure are vulnerable to a wide range of risks stemming from both physical and cyber threats and hazards. With the further expansion of the scope of cyberspace, e.g., information technology being increasingly integrated with physical infrastructure operations, computing and security still considered as one of the least investigated and exploited regions. In the past years, significant progress has been made with respect to advanced computing and endogenous security theories and technologies, and commercial advanced computing and endogenous security devices and systems are anticipated to become a reality in the near future.

A method for assessing cybersecurity in special-purpose information systems was developed. Cybersecurity assessment was performed using decision trees, implemented using “IF-THEN” fuzzy rules, which are considered as common building blocks of the decision tree. This approach allows processing large amounts of data. The use of the decision tree allows increasing evaluation accuracy, is easy to set up and intuitive. Improvement of the efficiency of cybersecurity assessment (error reduction) was achieved using evolving neuro-fuzzy artificial neural networks. Training of evolving neuro-fuzzy artificial neural networks was carried out by learning not only the synaptic weights of the artificial neural network, type, parameters of the membership function, but also by reducing the dimensionality of the feature space. The efficiency of information processing was also achieved through training the architecture of artificial neural networks; taking into account the type of uncertainty of information to be assessed; working with both clear and fuzzy products, and reducing the feature space. This reduces the computational complexity of decision-making and eliminates the accumulation of learning errors of artificial neural networks. The computational complexity of the method is on average 2 million calculations less compared to the known ones, and after 2 epochs, the learning error decreases. Cybersecurity analysis in general occurs due to an advanced clustering procedure that allows working with both static and dynamic data. Testing of the proposed method was carried out. The increase in the efficiency of cybersecurity assessment of about 20–25 % in terms of information processing efficiency was revealed

Virtual Dispersive Network (VDN) in preventing third party interception - a way of dealing with cyber threats. VDN is a unique approach to cybersecurity, wherein a signal is transmitted in short bursts or quantum packets, which can't be covertly read without disrupting their content. No one can intercept data sent to you without introducing some noise in it. In this study, we have explored the use of Virtual Dispersive Network in cybersecurity which is still an innovation in the fight against cyberattacks however is still shows considerable potential in reducing cyberattacks on wireless networks drastically.

It is established that the efficiency and reliability of information and telecommunication systems, in particular the networks that are part of them, significantly depends on the high level of protection of critical components. However, the constant improvement of the technical equipment of these systems requires the creation of new and improvement of existing methodological support for cyber security. One of the promising approaches is the development of a universal method of cybersecurity in the context of cyberattacks (influences, threats, etc.) and unauthorized access by unauthorized users to critical nodes (components) of information and telecommunications systems. Timely detection, prompt counteraction to cyber threats and unauthorized access to critical network components is a necessary component of ensuring a high level of cybersecurity of the information and telecommunications system as a whole, especially in the context of hybrid warfare and armed aggression by the Russian Federation. To this end, the article proposes a method of cybersecurity of critical components of information and telecommunications systems, which is based on the integrated application of monitoring the state of network nodes and user access to them, recording the facts of cyberattacks based on analysis of incoming (outgoing) traffic, timely detection of unauthorized access to and commission of cyber threats, as well as operational response to these attempts. The paper presents the results of verification of the proposed methods. To this end, the article proposes a method of cybersecurity of critical components of information and telecommunications systems, which is based on the integrated application of monitoring the state of network nodes and user access to them, recording the facts of cyberattacks based on analysis of incoming (outgoing) traffic, timely detection of unauthorized access to and commission of cyber threats, as well as operational response to these attempts. The paper presents the results of verification of the proposed method. It is shown that its application allows to quickly detect the facts of cyber threats and unauthorized access to critical components of information and telecommunication systems networks and effectively counteract these attempts.

Security and privacy of users have become significant concerns due to the involvement of the Internet of Things (IoT) devices in numerous applications. Cyber threats are growing at an explosive pace making the existing security and privacy measures inadequate. Hence, everyone on the Internet is a product for hackers. Consequently, Machine Learning (ML) algorithms are used to produce accurate outputs from large complex databases, where the generated outputs can be used to predict and detect vulnerabilities in IoT-based systems. Furthermore, Blockchain (BC) techniques are becoming popular in modern IoT applications to solve security and privacy issues. Several studies have been conducted on either ML algorithms or BC techniques. However, these studies target either security or privacy issues using ML algorithms or BC techniques, thus posing a need for a combined survey on efforts made in recent years addressing both security and privacy issues using ML algorithms and BC techniques. In this article, we provide a summary of research efforts made in the past few years, from 2008 to 2019, addressing security and privacy issues using ML algorithms and BC techniques in the IoT domain. First, we discuss and categorize various security and privacy threats reported in the past 12 years in the IoT domain. We then classify the literature on security and privacy efforts based on ML algorithms and BC techniques in the IoT domain. Finally, we identify and illuminate several challenges and future research directions using ML algorithms and BC techniques to address security and privacy issues in the IoT domain.

The world is now entering the 4th Industrial Revolution (IR4) and South Korea is the example that accepted the cutting-edge evolution as it is a country with the most wired in the world. Hence, this study intends to explore the initiatives taken by the government of South Korea in succeeding to encourage and expand internet users among South Korean by implementing an auxiliary cyber policy. This study will implement a qualitative method by focusing on the case study of South Korea. The researcher intends to examine the cyber policy made by the South Korean government and its effect on the increasing internet usage among South Korean. The findings show that there are demographic factors in influencing internet users and mechanisms taken by the government by collaborating with private agencies in influencing South Korean through media platforms about the benefits of using the internet as part of daily life despite its vulnerability in cybercrimes.

Problem and goal. The article discusses the victimological signs of crimes in the field of using information technology and cyber threats in the context of digitalization of modern society. The relevance of scientific and methodological research in the field of pedagogy on the problems of preparation for the implementation of victimological activities is emphasized. Methodology. The study is based on the analysis of major challenges of digital society and the internal logic of the development of applied victimology, which is mainly concerned with preventing victimization amid the threats to modern society. Results. Based on the analysis, the study lists and describes the types of existing cyber threats depending on the object of the attack, as well as legislative acts that define information security and cybersecurity. It is noted not only the relevance of considering new threats to the information society, which cause the need for the development of information security and cybersecurity as independent scientific areas of informatics and partly applied victimology, but also the development of terminology and criteria in this area, as well as the formation of professional competence in the education system of modern specialists in the field of professional victimological knowledge aimed at preventing cybercrime. Conclusion. To prevent cybercrimes and to ensure cybersecurity, victimological activities, a special component in the professional activities of modern subjects of different levels, should be developed and carried out.

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