Data Security Risks Research Articles

Digital Disruption in Indian Retail: Trends, Opportunities, And Challenges

This research paper examines the significant growth and transformation of the Indian Retail Industry, now ranked as the fifth-largest globally. This expansion is driven by rising incomes, shifting middle-class lifestyles, and improved digital connectivity. In this competitive environment, Indian consumers increasingly demand personalized and exceptional services. Digital transformation is identified as a key success factor, enabling retailers to adapt to changing customer behaviors. The surge in online shopping, propelled by smartphone usage, has reshaped the consumer-retailer dynamic, necessitating robust online presences and investments in data analytics for better customer insights. Transparency in supply chains and real-time inventory management have become essential for effective retail operations. The paper highlights key digital transformation trends, such as digitized in-store experiences and workforce empowerment, while acknowledging challenges like change management, skill shortages, and data security risks. Retailers are advised to implement change management strategies, develop talent acquisition plans, and invest in cybersecurity to ensure sustainable growth.

A Systematic Review and Multifaceted Analysis of the Integration of Artificial Intelligence and Blockchain: Shaping the Future of Australian Higher Education

This study explores the applications and implications of blockchain technology in the Australian higher education system, focusing on its integration with artificial intelligence (AI). By addressing critical challenges in credential verification, administrative efficiency, and academic integrity, this integration aims to enhance the global competitiveness of Australian higher education institutions. A comprehensive review of 25 recent research papers quantifies the benefits, challenges, and prospects of blockchain adoption in educational settings. Our findings reveal that 52% of the reviewed papers focus on systematic reviews, 28% focus on application-based studies, and 20% combine both approaches. The keyword analysis identified 287 total words, with “blockchain” and “education” as the most prominent themes. This study highlights blockchain’s potential to improve credential management, academic integrity, administrative efficiency, and funding mechanisms in education. However, challenges such as technical implementation (24%), regulatory compliance (32%), environmental concerns (28%), and data security risks (40%) must be addressed to achieve widespread adoption. This study also discusses critical prerequisites for successful blockchain integration, including infrastructure development, staff training, regulatory harmonisation, and the incorporation of AI for personalised learning. Our research concludes that blockchain, when strategically implemented and combined with AI, has the potential to transform the Australian higher education system, significantly enhancing its integrity, efficiency, and global competitiveness.

Tantangan dan Solusi Administrasi Kesehatan di Era Digital ( Tinjauan Literature Review atas Implementasi Teknologi )

The aim of this research is Challenges and Solutions of Health Administration in the Digital Era (Literature Review Review of Technology Implementation). This type of research is a literature study. Data collection with documentation. Data analysis with SLR. The results of the research Based on the literature review on challenges and solutions in health administration in the digital era, it was found that the implementation of health technology offers great opportunities to improve efficiency and quality of services, but is also faced with various obstacles. The main challenges include limited digital infrastructure, lack of skills of health workers in using technology, and patient data security risks. Proposed solutions include increasing investment in technology infrastructure, ongoing training for health workers, and implementing stricter data security policies. By addressing these challenges, technology can significantly improve the effectiveness of health administration and patient care

Evolution of AI in Smart Home Systems: A Comprehensive Review

The evolution of Artificial Intelligence (AI) has significantly transformed the landscape of smart home systems into a new era of convenience, efficiency, and personalized experiences. This paper provides an insightful exploration into the historical progression and contemporary developments of AI within smart home environments. Beginning with an overview of early automation technologies, we trace the evolutionary trajectory of AI's integration into smart homes, highlighting key milestones, breakthroughs, and paradigm shifts. Moreover, this paper also highlights the applications of AI in smart home ecosystems, including home automation, energy management, security surveillance, healthcare monitoring, and personalized assistance. Through advanced sensor technologies, ubiquitous connectivity, and cloud-based computing, AI-enabled smart home platforms offer seamless integration, interoperability, and scalability, paving the way for a more interconnected and intelligent living environment. Furthermore, we discuss the emerging trends and future directions shaping the evolution of AI in smart home systems. We also address the associated challenges and considerations, including privacy concerns, data security risks, ethical implications, and regulatory frameworks, which warrant careful attention and mitigation strategies.

The Rise of Fintech and How it Made India a Cashless Economy

This paper examines the rise of fintech and its impact on transforming India into a cashless economy. It highlights key drivers, such as the 2016 demonetization, that accelerated the adoption of digital payments, mobile wallets, and UPI. The study explores how fintech has improved financial inclusion in both urban and rural areas, focusing on Paytm as a case study. Despite fintech's success, challenges like financial illiteracy, data security risks, and fraud persist. The paper offers recommendations for enhancing financial literacy, improving data security, and expanding fintech adoption to sustain its growth and further boost India's digital economy.

Риски и возможности цифровизации учетноконтрольных процессов в субъектах малого предпринимательства

The article presents the identification of risks of digitalization of accounting and control processes in small business entities. The study of the consequences of the occurrence of data security risks when using digital tools, as well as a comparative analysis of the risks of digitalization of accounting and control processes in small and large enterprises allowed us to develop proposals to minimize the risks of data security in small businesses when digitalizing their accounting and control processes.

Enhancing Smart Healthcare Networks: Integrating Attribute-Based Encryption for Optimization and Anti-Corruption Mechanisms

This study investigates the feasibility and effectiveness of integrating Attribute-Based Encryption (ABE) into smart healthcare networks, with a particular focus on its role in enhancing anti-corruption mechanisms. The study provides a comprehensive analysis of current vulnerabilities in these networks, identifying potential data security risks. An anti-corruption mechanism is designed to ensure data integrity and reliability. The ABE approach is then empirically compared to other prominent encryption algorithms, such as Identity-Based Encryption, Data Encryption Standard, Advanced Encryption Standard, and Rivest-Shamir-Adleman algorithms. These methods are evaluated based on access latency, data transmission speed, system stability, and anti-corruption capabilities. Experimental results highlight the strengths of the ABE algorithm, demonstrating an average access latency of 31.6 milliseconds, a data transmission speed of 3.56 MB/s, and an average system stability of 98.74%. Furthermore, when integrated into anti-corruption mechanisms, ABE effectively protects against data tampering and misuse, ensuring secure data transmission. Compared to alternative algorithms, ABE offers a more efficient, secure, and stable solution for data management within smart healthcare networks, supported by its robust anti-corruption capabilities. This positions ABE as an optimal choice for safeguarding the integrity and security of healthcare data.

THE EFFECT OF DIGITALIZATION ON HUMAN RESOURCE MANAGEMENT PRACTICES: A BIBLIOMETRIC ANALYSIS

This study examines the intersection of digitalization and human resource management (HRM) practices through a bibliometric analysis. Utilizing the VOS Viewer program for quantitative analysis and supplemented by qualitative content reading, the research explores key trends, themes, and authorship patterns within the existing literature. The primary data source is the Web of Science database, yielding 268 relevant studies published between 2005 and 2023. Findings indicate a growing interest in the topic, particularly within the management discipline, and highlight key HRM practices impacted by digitalization, including recruitment, training and development, performance management, and career management. The analysis reveals that digitalization enhances HR efficiency, reduces costs, and supports learning and development, while also presenting challenges such as data security risks, skill gaps, and potential resistance to change. Co-authorship and citation networks identify influential authors and emerging research clusters. The study underscores the interdisciplinary nature of digital HRM research and calls for broader database inclusion to enhance future bibliometric studies.

Entrepreneurship in the era of society 5.0: Navigating digitalization for innovation and growth

Purpose: This study explores the symbiotic relationship between entrepreneurship and digitalization in Society 5.0, emphasizing the pivotal role of entrepreneurs in navigating and leveraging digital technologies to foster innovation and propel economic development. Research Methodology: This study uses quantitative methods to explore entrepreneurship in the era of Society 5.0, focusing on digitalization for innovation and growth. The population comprises entrepreneurs in Indonesia who use digital technology in their business. The sample comprised of 200 purposively selected entrepreneurs. Data were collected using an online questionnaire on the use of digital technology, innovation, and business growth. Data analysis, including validation, descriptive analysis, and SEM-PLS, was conducted using Smart PLS. The results are expected to provide insights into digital strategies for business innovation and growth. Results: The results highlight how entrepreneurs can leverage digital technologies, such as AI, IoT, and big data, to develop innovative products, improve operational efficiency, expand markets, and make better decisions. The benefits include global market access, improved customer experience, and better business sustainability. This makes entrepreneurs more competitive and responsive to market change. Limitations: Today's entrepreneurship faces limitations, such as technology dependence, adaptation difficulties, data security risks, and the digital divide. Entrepreneurs also encounter global competition, changing regulations, a lack of digital skills, poor technology infrastructure, and funding difficulties. Overcoming these challenges requires support from the government, the private sector, and educational institutions. Contributions: This research helps institutions develop digital policies and training programs, adds to the global literature on entrepreneurship in the Society 5.0, provides digital strategies for management, and improves entrepreneurs' competencies in utilizing digital technologies. It provides practical guidance to support business innovation and growth in the digital age.

Reinforcement learning-enabled swarm intelligence method for computation task offloading in Internet-of-Things blockchain

Blockchain technology, based on decentralized data storage and distributed consensus design, has became a promising solution to address data security risks and provide privacy protection in the Internet-of-Things (IoT) due to its tamper-proof and non-repudiation features. Although blockchain typically does not require the endorsement of third-party trust organizations, it mostly needs to perform necessary mathematical calculations to prevent malicious attacks, which results in stricter requirements for computation resources on the participating devices. By offloading the computation tasks required to support blockchain consensus to edge service nodes or the cloud, while providing data privacy protection for IoT applications, it can effectively address the limitations of computation and energy resources in IoT devices. However, how to make reasonable offloading decisions for IoT devices remains an open issue. Due to the excellent self-learning ability of Reinforcement Learning (RL), this paper proposes a RL enabled Swarm Intelligence Optimization Algorithm (RLSIOA) that aims to improve the quality of initial solutions and achieve efficient optimization of computation task offloading decisions. The algorithm considers various factors that may affect the revenue obtained by IoT devices executing consensus algorithms (e.g., Proof-of-Work), It optimizes the proportion of sub-tasks to be offloaded and the scale of computing resources to be rented from the edge and cloud to maximize the revenue of devices. Experimental results show that RLSIOA can obtain higher-quality offloading decision-making schemes at lower latency costs compared to representative benchmark algorithms.

Emerging South African smart cities: Data security and privacy risks and challenges

Background: Smart cities leverage advanced technologies such as the Internet of Things (IoT), fifth generation (5G) networks, and data analytics to enhance citizens’ quality of life, focussing on creating efficient, functional, and eco-friendly urban environments. While these initiatives offer significant benefits, there are ongoing concerns about data security and privacy.Objectives: This article investigates the data security and privacy risks and challenges in emerging South African smart cities. The objectives are to identify these risks, assess the effectiveness of current security measures, and contextualise these vulnerabilities within the South African and global contexts.Method: A qualitative approach was adopted, involving virtual interviews with 20 Subject Matter Experts (SMEs) through purposive and snowball sampling. The raw data were thematically analysed, revealing significant themes.Results: Emerging South African smart cities face several risks and challenges, including poor governance, a shortage of skills, a lack of awareness and training, insufficient funding, and a combination of these factors.Conclusion: The research highlights the importance of safeguarding individuals’ data and privacy in the context of smart cities, advocating the need for proactive measures to address these concerns.Contribution: This article promotes interdisciplinary dialogue, leading to more comprehensive solutions. In addition, exploring data security and privacy in emerging smart cities aids in understanding the implications of information management practices. Although the article focuses on emerging South African smart cities, the challenges discussed have global relevance.

Threats and Opportunities of Students’ Use Of AI-Integrated Technology (ChatGPT) in Online Higher Education: Saudi Arabian Educational Technologists’ Perspectives

This research study explored the perspectives of 20 educational technologists from four Saudi Arabian universities regarding the integration of AI-powered technology, particularly ChatGPT, into online higher education. The study used a qualitative research method that relied on the principles of theoretical sampling to select participants and conducted in-depth interviews to collect their insights. The approach taken for data analysis was thematic analysis, which uncovered a rich range of insights on both the challenges and opportunities associated with students’ use of AI-integrated technology in the context of online higher education. Ten significant challenges emerged that shed light on the complexities and intricacies of integrating AI-powered technology into educational environments. These challenges included issues related to technological infrastructure, pedagogical adaptation, and the need for comprehensive training programs to empower both teachers and learners. Additionally, eight threats were examined that highlighted concerns about data security, privacy, and potential risks associated with AI technology in educational institutions. This study not only provided a comprehensive overview of the current landscape of AI-integrated technology in Saudi Arabian higher education, but also provided valuable insights for education stakeholders, technologists, and policy makers. It underscored the necessity of proactive measures to mitigate challenges and threats while harnessing the opportunities presented by AI technology to enhance the quality and effectiveness of online higher education.

A REVIEW OF IMPLEMENTING AI-POWERED DATA WAREHOUSE SOLUTIONS TO OPTIMIZE BIG DATA MANAGEMENT AND UTILIZATION

This review examines the implementation of AI-powered data warehouse solutions to optimize big data management and utilization, analyzing 25 peer-reviewed articles published over the last decade. As organizations increasingly rely on vast amounts of data for strategic decision-making, traditional data warehousing techniques have struggled to keep pace with the volume, variety, and velocity of modern data. The integration of artificial intelligence (AI) into data warehousing processes has emerged as a critical advancement, enhancing data processing efficiency, accuracy, and scalability. This study synthesizes findings from the literature to highlight key benefits such as automated data extraction, transformation, and loading (ETL) processes, real-time analytics, and improved data quality through advanced cleansing and anomaly detection. Additionally, it identifies significant challenges including data security risks, integration complexities, and the need for specialized skills and substantial investments. The review concludes with recommendations for future research and practical applications, emphasizing the importance of strategic planning and robust security measures to fully leverage AI's potential in revolutionizing data warehousing.

Fuzzy Learning-Based Electric Measurement Data Circulation Monitoring and Security Risk Anomaly Evaluation

With the circulation of massive electric measurement data, data anomaly caused by security attacks imposes security risks on reliable operation of smart grid. Long short-term memory (LSTM) based data circulation monitoring and security risk anomaly evaluation has been intensively studied. However, some issues remain unsolved, including learning overfitting and large prediction error. In this paper, we investigate fuzzy learning to infer the abnormal level of security risk. In particular, an adaptive grey wolf optimization-LSTM-fuzzy petri network (AGWO-LSTM-FPN) based electrical measurement data circulation monitoring and security risk anomaly evaluation algorithm is proposed. Specifically, AGWO is utilized to optimize LSTM parameter updating and improve traffic prediction accuracy. Furthermore, FPN is combined with multi-dimensional monitoring indicators to enhance anomaly level evaluation. Simulation results illustrate the excellent performance of AGWO-LSTM-FPN.

Tantangan Etika dalam Pengelolaan Anggaran Negara dalam Era Transformasi Digital

Digital transformation has reshaped the challenges and strategies of managing national budgets. This era places transparency, accountability, integrity, and data security as its primary focus. The significance of transparency and accountability in the management of national finances, particularly through the adoption of information technology, presents opportunities to enhance the effectiveness of public services. However, these changes also bring ethical challenges, especially concerning data security. The success of digital transformation requires ethical leadership, an understanding of data security risks, and the implementation of stringent policies. The adoption of financial technology can expedite the digitization of public services, escalating the risks associated with data security and potential fraud. Therefore, strategic strategies are needed to ensure that budget management adheres to ethical principles and integrity. The active role of the government is crucial in ensuring that transparency and accountability remain top priorities. Concrete steps, such as interactive services through digital platforms, can increase public engagement. The importance of integrity and data security is acknowledged as a central point, with policies and practices supporting information security. Further research can explore the role of new technologies, such as artificial intelligence, in enhancing transparency and data security in the management of national budgets.

The Ethical Dilemma of Educational Metaverse

This review investigates the ethical issues of integrating Metaverse technology in educational settings. Our study reveals significant ethical considerations, including privacy concerns, data security risks, and the widening digital divide. We identified critical challenges such as user safety, intellectual property rights, and the ethical use of artificial intelligence. To address these challenges, we propose robust solutions including enhanced privacy protections, initiatives to bridge the digital divide, and frameworks to ensure safe and inclusive environments. Additionally, we underscore the necessity of developing new pedagogical frameworks and management models to effectively incorporate Metaverse technologies. Our findings suggest that while the Metaverse offers immense potential for revolutionizing education, maintaining ethical standards and thoughtfully mitigating potential risks is crucial. By implementing the proposed solutions, educational institutions can harness the full potential of Metaverse technology while safeguarding the interests of all stakeholders.

A Comprehensive Survey for Hiding Medical Data Based DNA Lossless Technique

The health information data includes reports on the patient’s condition, including addresses, names, tests, treatments, diagnoses, and medical history. It is sensitive information for patients, and all means of protection must be provided to prevent third parties from manipulation or fraudulent use. The goal of this paper presents studies of safeguard the transfer of sensitive data over an unsecured network using DNA techniques to enhance security. A comparison analysis is used to show the security issues of the various DNA-based data (ciphering, concealing, and compression) techniques that are studied and investigated. Also, in our study is to provide future researchers with the necessary knowledge to conduct data security research to develop or improve DNA-based data- ciphering, compression-hiding strategies that are more reliable, secure, and efficient. Thus, future researchers need to propose a trustworthy DNA-based data (ciphering, hiding, and compression) techniques. The result of our study appears the perceived vulnerability of medical data and health insurance to concerns of security as well as common security issues, also the nature of these common security concerns, for reducing medical data security risks.

Data security risks and their prevention: Latvian enterprises in the context of selected countries

Data security risks and their prevention: Latvian enterprises in the context of selected countries

Data Privacy and Security Risks in AI-Based Code Understanding

Data Privacy and Security Risks in AI-Based Code Understanding

Control of Personal Data and Cyber ​​Space by Global Digital Platforms in Relation to Indonesia's Digital Sovereignty

The dominance of foreign digital platforms in the application ecosystem within Indonesia poses significant implications for the sovereignty of the Indonesian state; the utilization of such foreign digital technologies results in the inadvertent surrender and delegation of citizen data to foreign entities for monitoring and processing purposes. This phenomenon has elicited concern among legal scholars, as the usage of foreign applications signifies the applicability of the legal frameworks from the countries of origin of these applications. This raises critical questions regarding the sovereignty of the Indonesian state, particularly concerning its ability to exert control over data and cyberspace in the context of global platforms. The methodological approach employed in this investigation is grounded in normative legal research, utilizing a conceptual framework that examines relevant legal statutes. The aggregation and distribution of personal data constitutes an infringement upon individual privacy rights, as the right to privacy inherently encompasses the prerogative to determine the provision of personal information. The strategic policies and initiatives undertaken by the Indonesian government to bolster national digital sovereignty can be realized through several measures: the implementation of comprehensive personal data protection standards to enhance national digital sovereignty, the establishment of an independent authority for personal data protection, the fortification of cybersecurity measures to mitigate data security risks, and the jurisdictional enforcement of cyberspace law towards achieving digital economic sovereignty. There exists a pressing need for extensive regulatory frameworks to safeguard personal data as an integral component of human rights. A balance must be struck in the management of personal data processing, ensuring the protection of rights and fostering awareness among data subjects, thereby facilitating the development of a secure digital economic ecosystem that offers legal certainty for enterprises and enhances consumer confidence. Furthermore, the establishment of equitable international personal data protection regulations is essential to support the advancement of the digital economy through arrangements governing cross-border data flow.