Privacy Issues Research Articles

Advertising Breaks the Privacy of WeChat Circle of Friends Analysis

With the rapid development of Internet technology and the popularity of smart phones, social media has become an indispensable part of People's Daily life. WeChat, one of the largest social media platforms in China, has gained popularity for its moments function due to its high degree of privacy and user viscosity. However, with the rise of the social media advertising market, the frequent appearance of advertising messages in WeChat moments not only disrupts the social experience of users, but also may cause users to worry about privacy leakage. This study aims to deeply analyze how advertisement delivery breaks the privacy of WeChat circle of friends, and explore the possibility of optimizing advertisement delivery strategy, including delivery quantity, delivery characteristics, target audience positioning and so on. Through the optimization strategy, the purpose is to reduce the intrusion of user privacy, improve user experience, and achieve a win-win situation between business interests and user privacy protection. Using questionnaire survey and hot list comparison, the study analyzed the impact of advertising on users' privacy perception, attitude and behavior. Suppose the results show that AD delivery breaks the privacy of WeChat moments to some extent, and users are put off by frequent and non-personalized ads. The study also found that gender, age, occupation and other factors have an impact on the perception of privacy in WeChat circle of friends. Based on the research results, marketing strategies and content suggestions for different user groups are proposed, in order to better safeguard users' privacy rights and social experience while ensuring the effect of advertising delivery and promote the sustainable development of social media platforms and advertising industry.

Digital Twins for Smarter Iranian Cities: A Future Studies Perspective

This study explores the future of Urban Digital Twin (UDT) in urban planning systems of developing countries, with a focus on Iran. Despite UDT's growing popularity, its implementation in developing countries is limited. The research identifies critical factors influencing UDT development, including organisational acceptance, urban infrastructure, policy and legislation, and technology and innovation. Using a futures studies approach, the study employs the Delphi method, MICMAC (Matrix Impact Cross-Reference Multiplication Applied to a Classification) technique, and SISMW (Strategic Uncertainties and Strengths Weaknesses Opportunities and Threats Matrix) methodologies to analyse these factors. The study reveals that international sanctions, organisational factors, technological factors, and infrastructure limitations hinder UDT development in Iran. However, UDT technology has the potential to transform urban planning in developing countries. The study provides a roadmap for collaboration between public and private sectors and research institutes to facilitate UDT implementation, highlighting the importance of legislative frameworks, digital infrastructure, innovation, and stakeholder engagement. Policy implications suggest that governments should prioritise supportive policies, investments in digital infrastructure, and collaborative efforts to address data privacy, security, and ownership issues. By addressing these challenges, developing countries can leverage UDT technology to improve urban planning, resource management, and quality of life.

Exploring barriers and facilitators to blood donation in secondary schools in Malawi.

Despite the Malawi Blood Transfusion Service (MBTS) increasing the amount of blood collected since its inception in 2004, Malawi remains with a 27% deficit in required blood supplies nationally. We sought to understand the facilitators and barriers to blood donation among secondary school students in Malawi. We utilised a qualitative exploratory design, with a sample of 135 participants purposefully selected from 16 secondary schools across Malawi. Data collection methods included in-depth interviews with 20 participants (inclusive of first-time and repeat donors, lapsed and non-donors), 20 key informant interviews (including community leaders, policy-level stakeholders and MBTS staff), and 16 focus group discussions involving 95 participants (community stakeholders and all donor categories). We used the consolidated framework for implementation research (CFIR) to assess barriers and facilitators of blood donation, focusing only on four CFIR domains: internal and external factors; the implementation process and individual characteristics influencing blood donation. Blood donation among students are facilitated by altruism, incentives including milestone awards, knowledge, motivation, transport, peer pressure and individual health status. Common barriers cited included: negative experiences with the blood donation process, fear, unsupported environment, poor incentives, privacy issues and the donation activities starting late than scheduled. While there have been efforts to motivate students to donate blood, significant barriers to blood donation still exist. Intensifying education and awareness campaigns may help dispel misconceptions and fears surrounding donation experiences and blood usage. Also, continuing with the provision of appropriate incentives including milestone awards may also encourage students.

Balancing privacy and public health: The impact of South Africa's cannabis legalization

The Cannabis for Private Purposes Act, enacted in South Africa in 2024, marks a significant shift in national drug policy by legalizing private cannabis use while aiming to balance individual privacy rights with public health and safety. This paper examines the Act’s impacts on socioeconomic dynamics, public health, and crime within South Africa, a context shaped by poverty, inequality, and strained healthcare resources. The study highlights potential economic benefits, such as job creation and formal market opportunities, alongside risks, including increased pressure on mental health services and complex implications for crime and gender-based violence. Drawing from government reports, recent studies, and international case comparisons, the analysis reveals how legalization might reduce the burden on the criminal justice system while also introducing challenges in public safety and healthcare capacity. The findings emphasize the need for robust governance frameworks that prioritize health system preparedness, social protections, and crime prevention. The discussion provides targeted policy recommendations for government agencies, healthcare providers, and law enforcement, addressing the importance of public education, regulatory oversight, and mental health support. This study offers valuable insights into the nuanced consequences of cannabis legalization in an emerging economy, contributing to global discussions on drug policy. By aligning policy with the realities of public health and safety, South Africa can leverage the potential benefits of legalization while mitigating its social costs.

Kewenangan Mahkamah Agung dalam Publikasi Pada Putusan Perkara Privat

This study examines the Supreme Court's authority to publish rulings on private cases and its impact on individuals' privacy rights. This authority, framed by transparency and data protection principles, is grounded in the right to public information per the Indonesian Constitution and Law No. 14 of 2008. However, publishing decisions in sensitive cases, such as divorce and domestic violence, risks violating individual privacy. This research addresses the urgent need to balance transparency and privacy by analyzing the legal basis and limitations on the Court’s authority. Through normative legal methods and legislative analysis, this study reviews key guidelines, including Supreme Court Decision No. 2-144/KMA/SK/VIII/2022, to recommend privacy protections for sensitive information in judicial rulings. Findings indicate that, despite a general obligation to disclose court decisions, exceptions must be made for sensitive data to safeguard privacy, contributing to a nuanced approach to judicial transparency.

Understanding the Role of Personalisation in Augmented Reality Applications for Enhancing User Experience

Purpose: The purpose of the study is to have an understanding about the impact of augmented reality (AR) on user experience in case of a makeup app. This article tries to explore how personalisation, an AR process, impacts the various aspects of user experience (pragmatic quality, hedonic quality by stimulation, hedonic quality by identification and attractiveness). This study also evaluates the moderating role of privacy concern on the relationship of personalisation and user experience. Methodology: This research empirically analyses data from an experiment conducted in a controlled lab setting with 200 valid responses from users of a makeup app, which incorporates AR technology. SPSS and SmartPLS4 were used for the analysis. Findings: The results show that personalisation significantly impacts the user experience, particularly in terms of enhancing pragmatic quality. However, the results did not show a moderating effect of privacy concerns on the relationship of personalisation and user experience. Implications: This research offers marketers a foundation on leveraging AR technology in enhancing the app experience. It also contributes to the AR literature by understanding the interplay of personalisation, privacy concern and user experience. Originality/Value: This study examines how personalisation in AR distinctly shapes the user experience. It also addresses the contemporary dilemma of privacy concerns, investigating whether marketers should prioritise enhancing personalisation or exercise caution to uphold user privacy. While previous studies related to AR and user experience have been conducted in Western contexts, this study is unique in its kind in India.

A community-based analysis of security practices regarding over-the-counter skincare products in nationwide retail drug stores.

Access to over-the-counter (OTC) skincare products is critical for managing a wide range of dermatologic conditions, yet recent trends in urban retail stores may jeopardize this accessibility and exacerbate healthcare disparities. However, the emerging trend of securing skincare products behind security glass in urban retail environments poses significant risks to healthcare equity and accessibility. Herein, we aim to quantify the prevalence of skincare products behind security glass in pharmacies within a 25-mile radius of Times Square, New York City. An observational, cross-sectional study was conducted, selecting 50 pharmacies from a total of 389 identified in the target radius. Digital photographs of skincare product aisles were taken, and the percentage of products secured behind glass was calculated for various categories and brands. The study found significant disparities in the availability of skincare products, with significantly higher percentages of products behind security glass in pharmacies located in urban areas compared to suburban regions. Among the four brands analyzed, Olay, L'Oréal, La Roche-Posay, and Vichy, there was no significant difference in the proportion of products behind security glass. Barriers to accessing skincare products, such as physical restrictions, time constraints, stigma, and privacy issues, may hinder individuals from obtaining necessary treatments, leading to potential delays in care and poorer health outcomes. Our study underscores the urgent need for dermatologists and healthcare policymakers to advocate for alternative security measures that do not compromise product accessibility. Facilitating easier access to OTC skincare products could dramatically improve treatment adherence and patient outcomes, particularly in urban settings where disparities are most pronounced.

The Role of Social Media in Enhancing Communication among Individuals: Prospects and Problems

This study is a discussion about the role that social media plays in enhancing communication among individuals, highlighting its prospects and related challenges. This research examines the impact of social media on improving communication among individuals and its prospects and challenges. This study had taken an integrated approach of secondary data analysis methodology through an extensive systematic review of the existing literature, along with the Canadian Research Data Collection (CREDC) national web-survey, to collect the attitudinal and behavioral insight of social media users on different platforms like Facebook, Twitter, and LinkedIn considering theoretical frameworks like Social Presence Theory and Media Richness Theory. Further, this conceptual review used PRISMA guidelines to examine how social media improves communication. Eligibility and exclusion criteria ensured peer-reviewed article selection and credibility. Study reveals that social media platforms significantly enhance interpersonal communication by fostering increased interconnectedness, more accessible information, and community formation. Notably, while these digital environments have considerable benefits, such as the facilitation of learning and support networks, they are also fraught with challenges, including misinformation, privacy concerns, and potential adverse effects on mental health. These findings therefore have dual approaches to reaping the benefits of social media in communication: the promotion of user education to reduce misinformation and building up digital literacy, while there is also a need to consider regulations that will protect against violation of privacy and cyberbullying. It is at this point that stakeholders will, arguably, have fewer difficulties in making use of social media to continue developing active citizenship and rich interpersonal relationships. Future research is encouraged to further explore the implications of emerging technologies on social media communication practices.

Consumer Adoption of Internet of ThingsIoT

ABSTRACTThe Internet of Things (IoT), a pivotal technology in enhancing user connectivity, faces a paradox: its widespread potential yet limited consumer adoption. This study addresses this dichotomy by synthesizing a large‐scale meta‐analytic structural equation modeling (MASEM) and hierarchical linear meta‐analysis (HiLMA) of 2736 effect sizes from 52,629 respondents across 138 studies. We propose an integrated and heterogeneous model, underpinned by appraisal theory and the technology acceptance model (TAM), to explain the dynamics of IoT adoption among consumers across heterogeneous settings. Our findings reveal that consumers' primary appraisals of IoT, influenced significantly by hedonic motivation and social influence, are instrumental in forming perceptions of IoT's ease of use and usefulness. These perceptions subsequently guide consumers in navigating the complexities of IoT, such as privacy, risk, and trust issues. These layered appraisals inform consumers' attitudes and intentions toward IoT adoption, wherein its efficacy is heightened in contexts involving critical services versus non‐critical ones, in Eastern versus Western regions, within healthcare rather than fashion sectors, and among more experienced and younger demographics, particularly students over the general public. The study also underscores the distinct impact of branded IoT devices over unbranded ones, delineating a heterogeneous understanding of IoT adoption. Therefore, the interpretation of heterogeneities in the combination of effect sizes from extant studies is a seminal attempt to address the IoT paradox by demonstrating which factors explain the variations in the relationship between attitude and intention toward IoT from the consumer's perspective.

Governance Considerations of Adversarial Attacks on AI Systems

Artificial intelligence (AI) is increasingly integrated into various aspects of daily life, but its susceptibility to adversarial attacks poses significant governance challenges. This paper explores the nature of these attacks, where malicious actors manipulate input data to deceive AI algorithms and their profound implications for individuals and society. Adversarial attacks can undermine critical AI applications, such as facial recognition and natural language processing, leading to privacy violations, biased outcomes, and eroding public trust. The discussion emphasizes understanding the threat vectors associated with adversarial attacks and their potential repercussions. It advocates for robust governance frameworks encompassing risk management, oversight, and legislative measures to protect AI systems. Such frameworks should prioritize AI technologies' confidentiality, integrity, and availability (CIA) while ensuring compliance with ethical standards. Furthermore, the paper examines various strategies for mitigating risks associated with adversarial attacks, including training and continuous monitoring of AI systems. It highlights the importance of accountability among developers and researchers in implementing preventive measures that align with principles of transparency and fairness. Organizations can enhance security and foster public trust by integrating legislative frameworks into AI development standards. As AI technologies evolve, continuous review of governance practices is essential to address emerging threats effectively. This paper ultimately focuses on the critical role of comprehensive governance in safeguarding AI systems against adversarial attacks, ensuring that technological advancements benefit society while minimizing risks.

Generative AI model privacy: a survey

The rapid progress of generative AI models has yielded substantial breakthroughs in AI, facilitating the generation of realistic synthetic data across various modalities. However, these advancements also introduce significant privacy risks, as the models may inadvertently expose sensitive information from their training data. Currently, there is no comprehensive survey work investigating privacy issues, e.g., attacking and defending privacy in generative AI models. We strive to identify existing attack techniques and mitigation strategies and to offer a summary of the current research landscape. Our survey encompasses a wide array of generative AI models, including language models, Generative Adversarial Networks, diffusion models, and their multi-modal counterparts. It indicates the critical need for continued research and development in privacy-preserving techniques for generative AI models. Furthermore, we offer insights into the challenges and discuss the open problems in the intersection of privacy and generative AI models.

The Future of Human Resources: How Technology is Shaping Workforce Management

In today's corporate world, technology is fundamentally altering HR departments. These technologies, such as artificial intelligence (AI), machine learning (ML), automation, and advanced data analytics, expand HR's capabilities from hiring and personnel management to performance reviews and employee engagement. This study investigates the ways in which these technologies affect personnel management and the strategic expansion of businesses. By using real-world examples and then analyzing the difficulties based on a survey of the literature, this research has brought attention to the strategic importance of implementing HR digitalization. However, despite the obstacles emerging from those paths - privacy issues, inadequacies in skill, and opposition to changes - the long-term efficiency achieved through decisionmaking and employee experience pushes the adoption of HR technology as an essential aspect of organizations. KEY WORDS: HR Technology, Artificial Intelligence (AI), Workforce Management,Machine Learning (ML), Data Analytics, Employee Engagement, Automation

Safe, Transparent, and Ethical Artificial Intelligence

The increasing integration of artificial intelligence (AI) into educational environments necessitates a structured framework to ensure its safe and ethical use. A manifesto outlining seven core principles for safe AI in education has been proposed, emphasizing the protection of student data, alignment with institutional strategies, adherence to didactic practices, minimization of errors, comprehensive user interfaces, human oversight, and ethical transparency. These principles are designed to guide the deployment of AI technologies in educational settings, addressing potential risks such as privacy violations, misuse, and over-reliance on technology. Smart Learning Applications (SLApps) are also introduced, integrating AI into the existing institutional technological ecosystem, with special attention to the learning management systems, enabling secure, role-adaptive, and course-specific learning experiences. While large language models like GPT offer transformative potential in education, they also present challenges related to accuracy, ethical use, and pedagogical alignment. To navigate these complexities, a checklist based on the Safe AI in Education principles is recommended, providing educators and institutions with a framework to evaluate AI tools, ensuring they support academic integrity, enhance learning experiences, and uphold ethical standards.

A regulatory gap analysis in transportation cybersecurity and data privacy

AbstractAlthough the need for regulatory and enforcement measures is dire, there is no all‐encompassing federal law or regulatory framework that governs cybersecurity or data privacy in the US transportation industry. The objective of this paper is to analyze the gaps that exist in US cybersecurity regulatory schematic as applied to transportation law and policy. As opposed to a theoretical approach, this study relies on a systematic gap analysis methodology to canvas a broad topic and distill specific insights that can be used as a foundation for establishing legislative and policy goals. Specifically, this paper attempts to answer: (i) what federal and/or state agencies are responsible for governing cybersecurity practices in the United States, including risk assessment, preventative measures, detection of breaches, and remedial enforcement; and (ii) how do industry experts assess the greatest risks/threats to ensuring cybersecurity in the transportation sector? The scope of selected legislative analysis is purposefully all‐encompassing of the transportation industry to highlight the scant nature of existing US law on the subject. Several states have enacted their own cybersecurity legislation, creating an unsynchronized approach nationwide that implicates jurisdictional issues, preemption problems, and inconsistent compliance requirements for national stakeholders. This paper next considers states' perspectives of transportation cybersecurity as assessed through a national survey of US state transportation agencies. Specific areas of concern identified as being important to the transportation industry but largely overlooked in the legislative spectrum include issues related to third‐party vendor liability, identifying cybersecurity tools, and supply chain risk management. Legislation covering workforce, ransomware, and cybersecurity‐related privacy issues saw more success, but low passage rates were still reflected with respect to the number of bills proposed. On the other hand, funding, insurance, and penalization issues appeared to be frequently prioritized. This paper presents the results of a gap analysis research approach identifying discrepancies between “what is” and “what should be” in transportation cybersecurity legislation.

Establishing Legal Frameworks to Address Criminal Misuse of AI

Artificial Intelligence (AI) is transforming numerous sectors in India, including the legal field. As AI technology becomes more widespread, concerns arise regarding its impact on criminal liability. This abstract examines the legal challenges and implications of AI’s involvement in criminal activities within the Indian context. The convergence of AI and crime raises complex questions about assigning criminal responsibility. The autonomous functioning of AI algorithms complicates accountability, making it difficult to determine liability for AI-related offenses. It emphasizes the significance of data privacy and security in the context of AI-driven criminal acts. Criminals may misuse AI to exploit personal data, underscoring the need for stringent data protection laws to protect individual privacy rights. Furthermore, AI-generated false content, such as deepfakes, raises concerns about evidence authenticity and the potential for manipulation in legal processes. The abstract also considers ethical issues surrounding AI’s role in criminal acts, stressing the urgent need for India’s legal system to address these complex challenges. By establishing comprehensive legal guidelines, encouraging ethical AI development, and strengthening data privacy measures, India can address AI- related criminal risks and promote responsible, secure technological advancement within the framework of criminal liability. Key Words: AI Misuse, Cybercrime, Legal Frameworks, Indian Penal Code, Information Technology Act, AI regulation, Cyber Law, Machine Learning

Perspectives of Patients Regarding Artificial Intelligence and Its Application in Healthcare: A Qualitative Study.

Artificial intelligence integration into healthcare has gained significant attention in recent years, with its use ranging from disease diagnosis to surgical assistance. While artificial intelligence's potential to improve patient outcomes and optimise patient care is undeniable, concerns regarding privacy, transparency, and the potential for medical errors persist. To take full advantage of artificial intelligence's transformative abilities, understanding patient perceptions and attitudes towards its integration into medicine is crucial for ethical considerations and health outcomes. This study aimed to describe patients' perceptions of medical artificial intelligence and its integration into the healthcare system, drawing attention to a crucial yet understudied aspect of artificial intelligence adoption in Kazakhstan. Descriptive qualitative design. From February to March 2024, the researchers conducted semi-structured interviews amongst 13 patients. The interviews were audio-recorded, transcribed, translated, and then analysed using a thematic analysis approach. The study adhered to the COREQ guidelines. Five themes emerged from 13 interviews: the benefits of artificial intelligence on patient care, the importance of human factors on patient care over artificial intelligence, revolutionising patient care delivery through artificial intelligence, patient education and artificial intelligence, and balancing technology and human interaction in artificial intelligence-driven intervention. Patient perceptions of artificial intelligence integration into healthcare were primarily positive. Nevertheless, patients prefer artificial intelligence as a supplementary tool under human supervision due to risks such as possible medical errors and violations of patient privacy. Patients provided the data for this study. The researchers interviewed them about their perceptions of medical artificial intelligence and its integration into the healthcare system. The patients or the public contributed nothing to the other aspects of the study.

Efficiency of Police Cooperation in Criminal Investigations

Police cooperation is essential not only to investigate crime, but also to prevent it. Sharing information and best practices between law enforcement agencies allows early identification of threats, which can lead to prompt and effective interventions. At the same time, working together can reduce legislative or procedural disparities between states, which helps to strengthen joint efforts to fight crime. In addition to legal and operational challenges, police cooperation also raises ethical, privacy and data protection issues. In the digital age, the exchange of information between police agencies must comply with strict data protection standards in line with national and international legislation, such as the General Data Protection Regulation (GDPR) in the European Union. Thus, police cooperation is an indispensable tool in criminal investigations, offering the possibility to go beyond the geographical and legal limits imposed by national borders. However, its effectiveness depends on a clear legislative framework, mutual trust between partners and the adoption of modern technologies to facilitate real-time communication and information exchange. Police cooperation is an essential element in the fight against contemporary crime, but its effectiveness depends on resolving the legislative and operational problems that sometimes prevent effective inter-agency cooperation. Technological development and adaptation to new forms of crime also remain major challenges in this area.

Navigating The Duality: Privacy And Security Concerns In Knowledge Management Systems (KMS)

This study delves into the intricate relationship between privacy and security within Knowledge Management Systems (KMS). It identifies and analyzes distinct employee perceptions of these intertwined issues within a company's KMS environment. By exploring these perspectives, the authors aim to dispel the confusion surrounding privacy and security in KMS settings. The research employed an explanatory sequential mixed method design. First, a questionnaire survey was distributed directly to KM staff across three companies. This was followed by semi-structured interviews with four KM staff members. The findings reveal a high level of employee awareness regarding the importance of KMS and, consequently, the significance of personal information privacy and security. The study further distinguishes between privacy and security concerns within KMS. Privacy concerns, differentiated across three dimensions: confidentiality, trust, and behavior, are primarily viewed from the organizational layer. Security aspects, on the other hand, are seen as aligned with the ICT layer, governed by legal frameworks and KMS architecture.

Evaluation of privacy protection methods of public service advertising visual design in the perspective of artificial intelligence internet of things.

With the widespread application of monitoring technology and network storage technology, there are some privacy issues in the process of public service advertising visual design and the process of pushing public service advertising visual design works. Researching the privacy protection method of public service advertising visual design is of great significance to protecting the privacy data security of public service advertising visual designers and the personal privacy of other citizens. This paper proposes a digital watermark privacy protection method and a public service advertising visual design work push privacy protection method, and conducts a privacy protection experiment study on public service advertising visual design. The digital watermark privacy protection method and the public service advertising work push privacy protection method are used to provide an innovative solution for public service advertising privacy protection. The study shows that the evaluation score of the digital watermark privacy protection method is 11.05% higher than that of the traditional passive privacy protection method; the average feasibility evaluation score and the average effectiveness evaluation score of the privacy protection method for the public service advertising visual design work push by experts are 86.8 and 90.66 respectively. Combining the perspectives of artificial intelligence and the Internet of Things, this paper proposes a digital watermark privacy protection method, emphasizing practicality, and providing new ideas for privacy protection of public service advertising visual design.

Security analysis and evaluation of mobile banking applications in Nigeria

Rapid fintech adoption across the world is so ubiquitous. To facilitate more adoption in Nigeria, recently the Central Bank of Nigeria (CBN) introduced several policies that support cashless banking. Nowadays, Nigerian banks users could perform most of their daily transactions from any desired location using mobile banking applications. In the literature, there are insufficient studies that comprehensively evaluate the security strength or risks of these applications. Generally, insecure mobile banking applications could lead to financial fraud, violations of privacy, identity theft and eroded user confidence. Considering the situation, there is need to conduct research which comprehensively assess security of the applications. Consequently, in this paper we analyzed and evaluated the security of identified popular mobile banking applications in Nigeria. We conducted the analysis work using automated and manual static analysis methods. Then, we evaluated the security of the applications using multi-criteria decision-making technique. Our results revealed that most of the applications have several security challenges in form of vulnerabilities and insecure coding practices. Hence, our findings have shown the applications need further improvements for better security and safety.