Cybersecurity Issues Research Articles

Unveiling the Ethical Dilemmas of Digital Piracy: A Comprehensive Exploration of Motivations, Attitudes, and Behaviors

Driven by several elements, including the unwillingness to pay for material, the spread of subscription services, and the profitability of illegal activity, digital piracy has grown to be a common problem in the contemporary world. Along with financial damages for businesses and content creators, this phenomenon has legal repercussions for individuals involved in piracy and cybersecurity issues. The effective fight against digital piracy depends on an awareness of the drivers and hazards connected with this illegal activity. With an eye towards a thorough knowledge of this intricate problem, in this study, the focus centers on the reasons, attitudes, and actions behind digital piracy. Through examining how people defend their behavior in particular situations, in this study, the aim is to clarify the ethical issues and decision-making procedures related to piracy—even among otherwise law-abiding people. Combining a variety of the relevant literature and ideas, including situation ethics theory, in this study, we seek to provide insights for legislators, business players, and academics eager to meet the difficulties presented by digital piracy. This study adds to the continuous discussion on lessening the detrimental effects of digital piracy on content creators, businesses, and cybersecurity by looking at the underlying reasons for piracy and supporting legal access to material. Along with a dearth of research on the origins and moral questions of digital piracy, there is a lot of contradictory material. By examining the factors behind this unlawful activity, clarifying the complex dynamics involved, and offering understanding of the causes of digital piracy, this study seeks to close a significant void in the knowledge. The findings of this study will enable individuals to develop strategies for handling this prevalent issue in the digital era. Developing successful interventions that can reduce this illegal conduct and safeguard the interests of content producers, businesses, and cybersecurity overall depends on an awareness of the reasons behind digital piracy. This study advances the knowledge of the difficulties presented by this global phenomenon by investigating the ethical issues and decision-making procedures related to digital piracy.

Beyond Technical Barriers: A Multidimensional Conceptual Framework for Understanding and Countering Cyber Scam Susceptibility

Cyber-attacks have become a serious global cybersecurity issue, affecting sectors such as petroleum, finance, health, and industry. The financial and banking sectors are particularly vulnerable, experiencing disproportionate harm due to the escalating complexity of digital threats. Recent academic efforts have focused on developing countermeasures, but these have primarily concentrated on technical solutions, which alone are insufficient. The persistent success of cyber-attacks highlights the need for a better understanding of human susceptibility to cyber scams. This research addresses the gap by investigating the psychological and social factors that lead individuals to fall for scam emails and links. It also explores how hackers exploit social engineering tactics to target victims and seeks to reverse these tactics to enhance protection. By understanding why people fall for cyber scams, the research aims to develop more effective cybersecurity measures, contributing significantly to the ongoing battle against cyber-attacks.

Problematic aspects of medical artificial intelligence. Part 2

The capabilities of artificial intelligence (AI) and machine learning are growing at an unprecedented pace. These technologies have many useful applications, from machine translation to medical image analysis. A large number of such applications are currently being developed, and an increasing number of such applications is expected in the long term. Unfortunately, weaknesses and other unpleasant aspects of AI have received insufficient attention. In this review, we consider a whole range of already known problems and possible risks associated with the use of innovative neural network technologies, paying special attention to the ways of preventing real dangers and potential threats in order to expand the range of stakeholders and profile experts involved in the discussion of current issues of medical AI cybersecurity, formation of responsible approach to the vulnerabilities of neural network platforms, increasing the reliability of equipment protection for its safe use, as well as the importance of legal and ethical aspects of regulating the use of AI. Despite certain challenges described in our review, it is clear that AI will be an important element of the healthcare future. As the population continues to age and the demand for healthcare services grows, neural networks are expected to drive healthcare very soon, especially in the areas of medical image analysis, virtual assistants, drug development, treatment recommendations and patients' data processing. We would like to emphasize that while we recognize the innovative role that digital technologies and AI can and should play in strengthening the domestic healthcare system, we should not overlook the importance of timely and accurate assessment of their beneficial or negative impact on the industry to ensure such management decisions do not unnecessarily divert our attention and resources from non-digital approaches and research. This article is a continuation of the article by Berdutin VA, Romanova TE, Romanov SV, Abaeva OP. Problematic aspects of medical artificial intelligence. Part 1. Sociology of Medicine. 2023;22(2):202–211. DOI: https://doi.org/10.17816/socm619132

Media Perspectives on Indonesian Policies against Illegal Online Gambling: A Framing Analysis

Online gambling is illegal in Indonesia, both legally and socially. Nevertheless, it has gained popularity among various segments of society, including teenagers, adults, and even government employees. This study aims to understand the media's perspective on the handling of online gambling in Indonesia. Utilizing Robert Entman's framing analysis theory, the research focuses on four elements: defining the problem, diagnosing the cause, making moral judgments, and providing treatment recommendations. The sample consists of news articles from Kompas.com between June 2023 and July 2024. The findings reveal that Kompas.com emphasizes government actions such as the arrest of gambling operators, online gamblers, and celebrities promoting online gambling as the defined problem. In diagnosing the cause, the reports highlight online gambling as a complex crime involving international networks and cybersecurity issues. The moral judgment presented by Kompas.com underscores the negative impacts of online gambling, press freedom, and societal morality. The treatment recommendations suggested include stringent enforcement and deterrent penalties, as well as international cooperation to eradicate online gambling in Indonesia.

Cyber Security Awareness Model Based on NIST (National Institute of Standards and Technology) for Secondary School Students in Malaysia

As cybersecurity issues surge, it highlights the pressing need for increased awareness. In our digitally interconnected world, where information technology underpins the lives of individuals, businesses, and even national security, the threat of cyberattacks looms large. To enhance national cybersecurity preparedness, there is a critical call to action: we must promote public awareness of cybersecurity issues and bolster the ranks of trained cybersecurity professionals. This research introduces a novel cybersecurity awareness model based on the National Institute of Standards and Technology (NIST). Its primary goal is to make NIST accessible to secondary school students pursuing ICT courses and their invaluable resource, the school counselling units. The model aims to instil cybersecurity awareness in secondary school students and guide them in choosing the most suitable higher education paths, particularly in the ICT and cybersecurity fields. The study comprises three phases. In the first phase, a systematic literature review (SLR) examines globally applicable cybersecurity education models. The second phase investigates the implementation of cybersecurity education for secondary school students in Malaysia. This includes interviews with school counselling units responsible for guiding students toward higher education and surveys of students in grades four and five enrolled in ICT courses. The third and pivotal phase focuses on developing the proposed model. It involves analysing and implementing the results of the SLR, mapping them to the NIST framework, and incorporating themes from interviews and surveys. As a tangible representation of the model, a mobile application prototype has been developed. The Cybersecurity Awareness Model empowers school counselling units to seamlessly integrate career exploration with career decision-making for secondary students at any stage of their development. Moreover, it offers a means to create strategies for after-school programs, particularly in the dynamic field of cybersecurity. This model is expected to guide students in exploring academic majors and careers, preparing for higher education post-high school, initiating internships or job searches, and adapting to a world in constant flux. In doing so, it not only empowers individuals but also strengthens the nation's resilience in the face of cybersecurity challenges.

New accents of security-oriented management of logistics activity entities in the conditions of digitalization

The paper focuses on management issues in the field of sustainable functioning and development of business entities on the basis of guaranteeing their economic security. The industry specialization of entities specializing in logistics activities is taken into account. New aspects of security-oriented management of logistics entities are defined and taken into account, in particular in the languages of digitalization, which bring to the fore the issues of information and cyber security, digital communications, as well as cashless electronic payments. On this basis, the purpose of the research is to identify new accents of security-oriented management of logistics entities in the conditions of digitalization. The components of the economic security of logistics entities that require priority attention in terms of strengthening during the digital transformation of the economy and society have been determined. The toolkit of safety-oriented management under modern conditions for subjects of logistics activity is indicated. It is shown that under modern conditions, business entities specializing in logistics activities should focus on two mega aspects when forming their own security-oriented management systems. These are: (1) operational challenges caused by critical instability and the consequences of a full-scale war; (2) new opportunities, realities, as well as challenges of global and comprehensive digital transformation of economic relations. It was concluded that the new emphasis of security-oriented management of logistics entities concerns all the leading components of their economic security.

Cybersecurity in Electric and Flying Vehicles: Threats, Challenges, AI Solutions & Future Directions

Electric and Flying Vehicles (EnFVs) represent a transformative shift in transportation, promising enhanced efficiency and reduced environmental impact. However, their integration into interconnected digital ecosystems poses significant cybersecurity challenges, including cyber-physical threats, privacy vulnerabilities, and supply chain risks. This paper comprehensively explores these challenges and investigates artificial intelligence (AI)-driven solutions to bolster EnFV cybersecurity. The study begins with an overview of EnFV cybersecurity issues, emphasizing the increasing complexity of threats in digital transportation systems. Methodologically, the paper reviews existing literature to identify gaps and assesses recent advancements in AI for cybersecurity applications. Key methodologies include AI-powered intrusion detection, threat analysis leveraging machine learning algorithms, predictive maintenance strategies, and enhanced authentication protocols. Results underscore the effectiveness of AI technologies in mitigating EnFV cybersecurity risks, demonstrating improved threat detection and response capabilities. The study concludes by outlining future research directions, highlighting the need for continued innovation in AI, quantum computing resilience, blockchain applications, and ethical considerations. These findings contribute to a clearer understanding of EnFV cybersecurity dynamics and provide a roadmap for enhancing the security and reliability of future transportation systems.

Reducing the risk of social engineering attacks using SOAR measures in a real world environment: A case study

The global cost of successful cyberattacks is increasing annually, with there being a shift towards social engineering threats in recent years. Cybercriminals are increasingly targeting humans rather than technical systems, recognizing data as a critical resource, especially in the finance industry where breaches can lead to substantial losses and reputational damage. The present case study proposes measures to reduce human susceptibility to social engineering attacks, leveraging SOAR (Security Automation, Orchestration, and Response) technology for incident response automation. The study covers various issues in cybersecurity, SOAR, and social engineering, through analyzing interviews with expert practitioners in the field, addressing cybersecurity skills shortages and current cyber threats. Four social engineering vignettes were developed, representing real threats, along with specific SOAR measures implemented using Microsoft Sentinel. These measures were simulated to demonstrate their effectiveness by reducing the employee's vulnerability to social engineering attacks. The risk of social engineering attacks was successfully reduced by implementing a responsive approach through the developed SOAR measures. Some of the measures reduced the risk by locking user accounts or forcing password changes after a detected cyber incident while another measure was developed for awareness enhancements. Given the current shortage of cybersecurity professionals, technologies like SOAR are becoming increasingly relevant for security teams. However, SOAR alone cannot address all challenges posed by social engineering and should be viewed as a complementary measure rather than a standalone solution.

Awareness of Cyber Security Issues among Social Media Users-A Study of Postgraduate Students

The rapid advancement of social media platforms has completely transformed everyday activities, especially among the younger generation. These platforms serve multiple purposes, providing both entertainment and serving as essential tools for communication and information dissemination. These platforms offer a wide range of features like augmented reality and interactive elements to cater to engage their audience. In Spite of their widespread use, concerns about privacy breaches and data violations continue to be a cause for concern. Despite the use of privacy protection tools, the number of breaches continues to rising. This study seeks to examine the awareness of cyber security issues and behaviors of postgraduate students on social media platforms. Using a descriptive research design, the primary data is gathered from a sample of 250 post graduate students selected at randomly from Karnataka State Akkamahadevi Women University, Vijayapura and Karnatak University, Dharwad. The primary data collected through a structured questionnaire. This study aims to address the privacy concerns in social media usage among postgraduate students.

Designing A Blockchain-Empowered Telehealth Artifact for Decentralized Identity Management and Trustworthy Communication: Interdisciplinary Approach.

Telehealth played a critical role during the COVID-19 pandemic and continues to function as an essential component of health care. Existing platforms cannot ensure privacy and prevent cyberattacks. The main objectives of this study are to understand existing cybersecurity issues in identity management and trustworthy communication processes in telehealth platforms and to design a software architecture integrated with blockchain to improve security and trustworthiness with acceptable performance. We improved personal information security in existing telehealth platforms by adopting an innovative interdisciplinary approach combining design science, social science, and computer science in the health care domain, with prototype implementation. We used the design science research methodology to implement our overall design. We innovated over existing telehealth platforms with blockchain integration that improves health care delivery services in terms of security, privacy, and efficiency. We adopted a user-centric design approach and started with user requirement collection, followed by system functionality development. Overall system implementation facilitates user requirements, thus promoting user behavior for the adoption of the telehealth platform with decentralized identity management and an access control mechanism. Our investigation identified key challenges to identity management and trustworthy communication processes in telehealth platforms used in the current health care domain. By adopting distributed ledger technology, we proposed a decentralized telehealth platform to support identity management and a trustworthy communication process. Our design and prototype implementation using a smart contract-driven telehealth platform to provide decentralized identity management and trustworthy communication with token-based access control addressed several security challenges. This was substantiated by testing with 10,000 simulated transactions across 5 peers in the Rahasak blockchain network. The proposed design provides resistance to common attacks while maintaining a linear time overhead, demonstrating improved security and efficiency in telehealth services. We evaluated the performance in terms of transaction throughput, smart contract execution time, and block generation time. To create a block with 10,000 transactions, it takes 8 seconds on average, which is an acceptable overhead for blockchain-based applications. We identified technical limitations in current telehealth platforms. We presented several design innovations using blockchain to prototype a system. We also presented the implementation details of a unique distributed architecture for a trustworthy communication system. We illustrated how this design can overcome privacy, security, and scalability limitations. Moreover, we illustrated how improving these factors sets the stage for improving and standardizing the application and for the wide adoption of blockchain-enabled telehealth platforms.

USING DIGITAL PLATFORMS FOR REPORTING IN THE IMPLEMENTATION AND EVALUATION OF ESG STRATEGIES

The article discusses modern approaches to using digital platforms for reporting and, implementing and evaluating ESG strategies. The role of environmental, social, and governance (ESG) factors in ensuring the sustainable development of enterprises and society is analyzed. The importance of implementing digital platforms for collecting, processing, and analyzing data, which allow for increased efficiency and transparency of reporting, has been proven. The main advantages and challenges facing enterprises using such platforms are characterized mainly by increasing the trust of investors and other interested parties. The use of digital platforms in reporting allows for the automation of data collection processes, integrating various sources of information into one system. This significantly reduces the risk of errors and increases the accuracy of data, which is crucial for making informed management decisions. The article also addresses the issues of transparency and credibility of reporting, which are ensured by process automation and the use of technologies such as blockchain. This helps to increase the trust of investors and other stakeholders, improve the company’s reputation, and attract additional investments. A significant advantage of digital platforms is their integration with existing management systems, which saves existing IT infrastructure investments and reduces the costs of introducing new technologies. However, implementing digital platforms is not without challenges. These include cybersecurity issues, the protection of confidential data, the high costs of implementing new technologies, and the need to adapt existing business processes to new conditions. The article presents the successful use of digital platforms for reporting in the agro-industrial sector, positively impacting management and decision-making processes. The study concluded the development prospects of digital technologies in ESG reporting and their importance for long-term economic growth and sustainable development. Integrating digital platforms into reporting processes contributes to increased efficiency, transparency, and data reliability, ensuring the sustainable development of business and society.

A framework for evaluating the barriers to adopting Industry 4.0 in Indian SMEs: an approach of best-worst method

This study aims to highlight the need for Industry 4.0 in a manufacturing system and explore the importance of the barriers to adopting Industry 4.0 technologies in Indian SMEs. Many barriers to implementing Industry 4.0 were explored through a literature review. These barriers are prioritized using the Best-Worst Method (BWM). The framework has illustrated the approach to exploring the barriers and ranking these barriers based on feedback from industry experts. Some of the barriers such as lack of infrastructure, lack of financial resources, lack of government initiatives, high complexity, and cyber security and data ownership issues are observed to be very influential in SMEs to adopting Industry 4.0. The proposed framework can also be used in other industries for implementing Industry 4.0 technologies. Prioritizing and overcoming the barriers step-by-step may help the manager to digitalize the systems.

Comprehensive review of smart city cybersecurity strategies

With cities rapidly advancing technologically, the rise of smart cities brings innovative solutions to urban challenges. However, this integration of technologies within urban infrastructures introduces new cybersecurity risks. This review explores the cybersecurity issues that smart cities face and discusses strategies to address these threats. Smart cities rely on interconnected networks of devices and systems to enhance efficiency, sustainability, and citizen services. Yet, this connectivity also creates a complex environment that is vulnerable to cyberattacks. A key concern is the wide array of IoT devices deployed across smart city infrastructures, which often lack robust security mechanisms, making them susceptible to exploitation by cybercriminals. The interconnected nature of these systems heightens the potential impact of cyberattacks, posing significant risks to critical infrastructure, public safety, and privacy. Threat actors can exploit vulnerabilities in interconnected systems, disrupting essential services, manipulating data, or even causing physical harm. Since smart cities heavily depend on data-driven decision-making, ensuring data integrity and confidentiality is a top priority. To mitigate these risks, various cybersecurity strategies have been proposed and implemented. These include technical solutions, regulatory frameworks, and collaboration among stakeholders. Technical measures like encryption, authentication mechanisms, intrusion detection systems, and secure software development practices are essential. Additionally, strong access controls and network segmentation can limit the scope of potential attacks. Regulatory initiatives also play a crucial role in improving cybersecurity standards and ensuring compliance among stakeholders. Establishing clear guidelines for data protection, privacy rights, and incident response protocols is vital for safeguarding citizens' interests. Collaborative efforts between government agencies, the private sector, academia, and cybersecurity experts are crucial in sharing information and collectively defending against emerging threats. Securing smart cities requires a comprehensive approach that integrates technical measures, regulatory frameworks, and collaborative efforts to create a resilient and secure urban environment for all citizens. Keywords: Cybersecurity, Smart City, AI, Technology, Security.

Issues of Cyber security and its solutions in Nepalese Context

In today's digital age, the internet's expansion has brought great convenience but also raised cyber threats. So, identify the issue of cyber-security and its solution in Nepalese context is significant. Descriptive design and qualitative methods were employed, with data sourced from Google Scholar and analyzed through thematic analysis. The study shows a myriad of issues stemming from inadequate cyber security awareness in Nepal, including increased vulnerability to cyber-attacks, data breaches, and societal, economic, and regulatory consequences. Bridging the gap in cyber security awareness is imperative to mitigate risks effectively and foster a secure digital environment in Nepal. Strategies emphasizing education, training, and regulatory frameworks are vital for addressing these challenges and promoting technological advancement and societal trust. This study proposes AI-driven solutions to address the lack of cyber security awareness in the Nepalese context, offering a unique approach to mitigate cyber threats and foster a secure digital environment.

Advanced Threat Recognition: Harnessing Machine Learning for Intrusion Detection

Conventional intrusion detection systems (IDS) are frequently inadequate to combat complex cyber threats in the changing cybersecurity landscape. To create a reliable intrusion detection system, this work investigates the use of machine learning, more especially the RandomForestClassifier method. The study highlights that in order to maximize model training, careful data preprocessing—including feature selection, label encoding, and scaling—is essential. It also uses Optuna for hyperparameter adjustment to improve the classifier's performance. As a scalable and dependable response to contemporary cybersecurity issues, the findings show how effective machine learning is in identifying sophisticated attacks. The outcomes show a high detection accuracy and resilience to complex intrusions, confirming machine learning's potential as a scalable and reliable answer to today's cybersecurity problems

GSAAN with War Strategy Optimization Algorithm for Cyber Security in a 5G Wireless Communication Network

In this paper, the graph sample and aggregate-attention network with war strategy optimization algorithm for cyber security in the 5G wireless communication network (CS-5GWCN-GSAAN-WSOA) is proposed in 5G mobile networks to identify cyber threats. Initially, the input data are amassed from the 5G-NIDD dataset. Then the input data are fed to preprocessing, here redundancy elimination and missing value replacement are performed utilizing the contrast limited adaptive histogram equalization filtering (CLAHEF) method. After preprocessing, optimal features are selected by the stochastic gradient boosting based recursive feature elimination process. The selected features are fed to the graph sample and aggregate-attention network (GSAAN) to detect cyber-attacks in 5G wireless communication. Generally, the GSAAN approach does not adopt any optimization techniques for determining optimal parameters and guaranteeing accurate attack detection. Therefore, the war strategy optimization algorithm (WSOA) contemplates to optimize the GSAAN weight parameters. The CS-5GWCN-GSAAN-WSOA method is activated on Python. The CS-5GWCN-GSAAN-WSOA method attains 22.51%, 20.35%, and 35.54% higher accuracy, 19.45%, 27.80%, and 18.93% higher sensitivity analysed with existing models, like cyber security attack identification in 5G wireless systems utilizing machine learning (CS-5GWCN-SVM), enhanced dropping attacks detection in 5G networks depending on deep learning models (CS-5GWCN-KNN), and cyber security issues in 5G enabled attack detection through deep learning (CS-5GWCN-RNN), respectively.

The use of artificial intelligence in the management of investment portfolios

The ever-increasing complexity of financial markets, characterized by high market volatility, economic uncertainty, and the massive influx of various data pose a significant challenge in investment portfolio management. Traditional methods can fall short in addressing these challenges, requiring too much from an individual managing investment portfolios. The ability of AI to process a tremendous number of large datasets and to detect patterns offers a significant advantage for a manager, providing for more informed and timely investment decisions. The purpose of this annex is to encapsulate findings of the primary paper on the use of AI in investment portfolio management, highlighting the benefits and challenges, and also identifying areas for improvement and further research. The paper explores the possibility of using AI to enhance the effectiveness of an investment portfolio manager, through the improvement of analysis’ quality, help in data collection and processing, recognition of complex patterns, and faster decision-making. This could help optimize investment strategies through risk reduction, improved forecasting, and faster adaptation to market fluctuations. In addition, the paper aims to identify potential risks associated with AI integration, for example quality of data, algorithm transparency, and cybersecurity issues. Literature analysis demonstrated that application of AI can increase the efficiency of investment portfolio management. This is possible because of AI systems' ability to conduct advanced data search and analysis, providing for better decision-making. The use of AI algorithms allows investment portfolio managers to identify market trends more easily, optimize asset allocations, as well as minimize market volatility risks. А good example is BlackRock's Aladdin expert system, which provides comprehensive data insights, providing a competitive advantage. However, the paper also demonstrates, that implementation of AI systems is associated with several challenges, particularly - quality of provided data and opacity of AI algorithms, which can raise doubts regarding their effectiveness. Moreover, cybersecurity remains a significant concern. Overall, the use of AI presents opportunities for investment portfolio managers to improve results by providing competitive advantages. However, certain challenges need to be overcome. AI holds great promise for investment portfolio management, and future studies need to focus on AI integration, cybersecurity, and improvement of data quality.

Enhanced Prairie Dog Optimization with Differential Evolution for solving engineering design problems and network intrusion detection system

This paper introduces a novel hybrid optimization algorithm, PDO-DE, which integrates the Prairie Dog Optimization (PDO) algorithm with the Differential Evolution (DE) strategy. This research aims to develop an algorithm that efficiently addresses complex optimization problems in engineering design and network intrusion detection systems. Our method enhances the PDO's search capabilities by incorporating the DE's principal mechanisms of mutation and crossover, facilitating improved solution exploration and exploitation. We evaluate the effectiveness of the PDO-DE algorithm through rigorous testing on 23 classical benchmark functions, five engineering design problems, and a network intrusion detection system (NIDS). The results indicate that PDO-DE outperforms several state-of-the-art optimization algorithms regarding convergence speed and accuracy, demonstrating its robustness and adaptability across different problem domains. The PDO-DE algorithm's potential applications extend to engineering challenges and cybersecurity issues, where efficient and reliable solutions are critical; for example, the NIDS results show significant results in detection rate, false alarm, and accuracy with 98.1%, 2.4%, and 96%, respectively. The innovative integration of PDO and DE contributes significantly to stochastic optimization and swarm intelligence, offering a promising new tool for tackling diverse optimization problems. In conclusion, the PDO-DE algorithm represents a significant scientific advancement in hybrid optimization techniques, providing a more effective approach for solving real-world problems that require high precision and optimal resource utilization.

Environmental, Social, and Governance-Based Artificial Intelligence Governance: Digitalizing Firms’ Leadership and Human Resources Management

The integration of artificial intelligence (AI) with environmental, social, and governance (ESG) factors is impacting the direction of enterprises and society in our swiftly expanding world. This collaboration has significant potential to tackle critical issues such as reducing the impact of climate change, fostering social integration, and improving corporate governance. Nevertheless, the implementation of AI gives rise to intricate matters and apprehensions, as it brings out a distinct array of hazards and ethical quandaries for ESG performance. The objective of the present research is to fill this gap by gathering and offering a contemporary evaluation of the influence of advancing technologies on the strategic leadership’s role in fulfilling the business goal within the context of ESG considerations. We used bibliometric analysis to investigate the study subject using R Studio version 4.2.0 and the bibliometric applications VOSviewer version 1.6.20 and Biblioshiny version 4.2.0. We obtained data from the Scopus database and used the PRISMA approach to suitably choose 205 research publications. The results suggest that it is essential to use AI and ESG to digitize the boardroom. Additionally, it is crucial to guarantee its security using an advanced detection system. Therefore, chief executive officers (CEOs) must give priority to the issues of transparency and cybersecurity to reduce risks and successfully inspire trust in business activities.

Cybersecurity Awareness Model with Methods: Analytical Hierarchy Process and Structural Equation Model

This era of revolution has influenced all sectors of society, including education, where technological advancements are now integral to online teaching and learning. However, not everyone fully understands the potential negative impacts of internet usage. The purpose of this research was to investigate and analyze cybersecurity awareness. The study focused on students at Aerospace Air Marshal Suryadarma University. The research employed a quantitative design, either descriptive (where subjects are typically measured once) or experimental (where subjects are measured multiple times). A descriptive study establishes a relationship between variables, while an experimental study determines causation. To analyze the collected data, SEM AMOS was utilized to measure students' awareness of cybersecurity. The study focused on five key areas: (a) regulation, (b) internet usage, (c) password security, (d) data security, and (e) cyberattacks. Based on the research framework and these focus areas, several indicators were developed for the study. The findings concluded that students are aware of cybersecurity issues.