Information Privacy Research Articles

Demand Analysis of Self-Management Mobile Health Applications for Middle-Aged and Older Patients with Chronic Kidney Disease Based on the Kano Model

Introduction: Middle-aged and older individuals often face significant challenges in adopting digital health solutions, leading to a digital divide that hinders their ability to benefit from mobile health (mHealth) interventions. This study aimed to investigate the specific requirements of middle-aged and older patients with chronic kidney disease (CKD) for self-management through mobile health applications (mHealth apps), using the Kano model. Methods: A multicenter cross-sectional survey was conducted from April to September 2023 in five hospitals across Sichuan, Shandong, Guangdong, and Shaanxi provinces in China. The Kano model was employed to analyze participants’ preferences regarding mHealth apps for self-management. Results: Out of 359 participants (57.1% men, predominantly aged 45–54), the study identified essential and desirable features for mHealth apps. Essential attributes include comprehensive CKD information and robust privacy protection. Key to enhancing user satisfaction is features like symptom and medication management, access to medical insurance information, and app interface simplicity. Additional attractive features for increasing app appeal include diet management, exercise guidance, and customizable text size. Conclusion: This study identifies critical mHealth app features for self-management in middle-aged and older CKD patients, emphasizing the importance of user-centric design. The findings provide valuable insights for app developers to create tailored solutions that cater to the specific needs of this demographic, potentially enhancing their self-management capabilities.

Decoding privacy concerns: the role of perceived risk and benefits in personal health data disclosure

BackgroundPersonal health data is crucial for effective medical care, personalized treatment, and health monitoring. It enables accurate diagnosis, efficient treatment plans, and informed healthcare decisions. Personal health data should be protected to ensure patient privacy, prevent misuse or unauthorized access, and maintain trust in healthcare systems, thereby safeguarding individuals’ sensitive information from potential harm or exploitation. Therefore, this study aimed to investigate whether perceived risk and perceived benefits have mediating roles in the relationships among individuals’ personal health information disclosure behaviour, perceived control, and privacy concerns.MethodThe population of the study consisted of individuals living in the provinces of Izmir, Konya and Adana. The sample of the study consisted of individuals who were reached through a convenience sampling method. The scales for privacy concerns, perceived control, perceived risk, perceived benefits and information disclosure behaviour were used in the study. Cronbach’s alpha and the AVE were calculated, and a confirmatory factor analysis was performed. A path analysis was performed using the structural equation model to test the hypotheses.ResultsThe analysis revealed a significant negative relationship between individuals’ personal health data disclosure behaviour and their privacy concerns. However, perceived risk and perceived benefit did not mediate this relationship. Additionally, a significant positive relationship was found between individuals’ behaviour of disclosing their perceived control and personal health data, with perceived risk and benefits playing a mediating role in this relationship.ConclusionThe study concluded that as individuals’ concerns about sharing personal health data increase, they are less likely to share these data. It was also found that perceived risk and perceived benefit mediate this relationship. Additionally, higher perceived risk intensifies privacy concerns, further discouraging data sharing, while perceived benefits can mitigate these concerns, promoting greater willingness to disclose health information.

Imprisoned at Work: The Impact of Employee Monitoring on Physical Privacy and Individual Liberty

There are now a wide range of tools available to monitor employees, boasting sophisticated features like keystroke logging, geolocational tracking and video surveillance. From a legal perspective, employee monitoring is most commonly analysed in terms of the impact it has on an employee's control over their information and data, ie their ‘informational privacy’. This article argues that monitoring is a more complex and layered issue, requiring the consideration of other values as well. Specifically, we argue that there are two (by no means exhaustive) reasons why employee monitoring is concerning which go beyond the use of information and data. First, monitoring affects physical and spatial, not just informational, components of privacy. Second, monitoring can be so severe in extreme cases that it curtails individual liberty and constitutes a form of imprisonment. The article draws out the significant legal implications of each of these claims, while addressing counterarguments to our position based on employee consent and the idea that work has always involved constraints on individual freedom.

Design of a Decentralized Authentication and Off-Chain Data Management Protocol for VANETs Using Blockchain

In the evolving landscape of Intelligent Transportation Systems (ITS), the need for secure and reliable data sharing is more critical than ever. As ITS increasingly rely on the exchange of sensitive information, challenges related to data privacy, security, and the integrity of communication have emerged. Traditional approaches to securing vehicular networks often depend on centralized Trusted Third Parties (TTP) and cloud-based infrastructure, which introduce vulnerabilities such as single points of failure and potential latency issues. This paper proposes a novel decentralized architecture for Vehicular Ad-Hoc Networks (VANETs) that enhances security by eliminating the dependency on centralized cloud servers. The proposed protocol leverages blockchain technology to facilitate secure off-chain storage of event data and implements a decentralized authentication mechanism. This approach ensures that the privacy and integrity of shared information are maintained without compromising the efficiency of the system.

Unveiling Mobile Wallet Adoption: Exploring UTAUT's Influence on Behavioral Intentions

In today’s world, smartphones have become the most important part of life. It has changed the lifestyles of many people. In recent times, the usage of smartphones has increased dramatically as it offers various benefits to its users. The rapid evolution of digital payment technologies has propelled the emergence of mobile wallets as a convenient and potentially transformative means of financial transactions. The current research focuses on analyzing the effects of UTAUT on users’ behavioral intentions for using Mobile wallet technology. In this empirical study, the main concepts of the UTAUT model are explained. Adopting the UTAUT framework, the survey evaluates important factors that influence users' intentions to adopt mobile wallets. This study uses survey data from 110 Internet users, which will be examined using regression, correlation, and weighted mean analysis. This research revealed positive significant correlation between intention and performance expectations, effort expectations, social norms, and privacy. However, it was also found that performance expectation, effort expectation and privacy of personal information had a significant positive influence on behavioral intention.

A secure blockchain framework for healthcare records management systems

AbstractElectronic health records are one of the essential components of health organizations. In recent years, there have been increased concerns about privacy and reputation regarding the storage and use of patient information. In this regard, the information provided as a part of medical and health insurance, for instance, can be viewed as proof of social insurance and governance. Several problems in the past few decades regarding medical information management have threatened patient information privacy. In intelligent healthcare applications, the privacy of patients' data is one of the main concerns. As a result, blockchain is a severe necessity as it can enhance transparency and security in medical applications. Accordingly, this paper uses the design science method to propose a secure blockchain framework for healthcare records management systems. The proposed framework comprises five components: a blockchain network, smart contracts, privacy key management, data encryption, and integration with healthcare information technology. In the proposed framework, healthcare organizations can manage healthcare information securely and privately. Additionally, a secure storage system for electronic records is proposed to meet these organizations' needs. It provides security and privacy for healthcare organizations, especially when managing healthcare information, and also proposes a secure storage system for electronic records to meet the needs of the organizations.

Deep Secrecy: Advancing Image Steganography Via Deep Learning Technique

In today's internet-driven world, while seamless connectivity and social media make tasks easier, they also bring risks like hacking and data theft. Steganography is an emerging field that hides various data types such as images, videos, texts, and audio to protect sensitive information shared online. This term, derived from the Greek words "steganos" (hidden) and "graph" (writing/drawing), reflects the essence of this practice: hiding messages in plain sight. This technique combines science and art to ensure information concealment, addressing the growing need for secure data exchange. To deal with the data theft issues the proposed methodology presents a novel Image Steganography technique using 2 networks one is the hiding network and the other is the revealing network built on the foundation of CNN-based UNeT Architecture. Equipped with specialized encoder and decoder components, the proposed model masterfully hides secret pictures within cover images, all while preserving the cover image's natural quality. The hiding network hides the secret image within the cover image and generates the stegano image while the revealing network extracts the secret image from the cover image and reveals the original secret image. The dataset used in this research is the “COCO dataset” from where random 7500 images were used to train the model. The proposed model successfully produced a Peak Signal Noise Ratio (PSNR) value of 41.08 db. The goal is to produce undetectable stego images making its detection practically difficult.

The Pivotal Role of Libraries in Sustainable AI Development

Artificial Intelligence (AI) has gained exceptional public and media coverage since the launch of the ChatGPT platform, a generative conversational intelligence, in November 2022. Nevertheless, AI is already an integral part of our digital daily lives, as we navigate through social networks, use our GPS, or consult recommendations on e-commerce websites. Due to its pervasive influence across all sectors of our societies, AI is gradually becoming a pivotal subject in terms of regulation, societal direction, and legislation. As early as 2021, UNESCO published a report presenting avenues for ethical considerations in AI. In June 2023, the European Union also established a regulatory framework outlining requirements and obligations for AI usage. As a digital manifestation and given the "new ways in which its use influences human thinking, interaction and decision-making and affects education, human, social and natural sciences, culture, and communication and information" (UNESCO. General Conference, 41st, 2021), public libraries have a role to play in enabling residents within their communities to grasp this technology. Their role is all the more significant as AI generates concerns and distrust (Gillath et al., 2021) among populations when "libraries also continue to enjoy a high level of trust and appreciation in most of their communities" (Arlitsch \& Newell, 2017). Understanding AI thus constitutes a new cornerstone for accessing the necessary information to advance sustainable development, as outlined in the Lyon Declaration (2014). Moreover, comprehension of AI aligns with the ethical concerns articulated by UNESCO in terms of explainability and transparency and aligns with several Sustainable Development Goals (SDGs) of the 2030 Agenda. These goals include quality education (4), industry, innovation and infrastructure (9), reduced inequalities (10), sustainable cities and communities (11), as well as responsible consumption and production (12). The role of public libraries in advancing the goals of the 2030 Agenda is beyond dispute (IFLA, 2016), and various digital literacies are already integral to their actions. As AI is predominantly developed by global economic giants and permeates all of our practices, "Shouldn’t [libraries] be the bastions of information literacy and information privacy in an AI world?" (Cox et al., 2018). Thus, to what extent can public libraries take on this subject to promote and offer relevant literacy? For this study, we will conduct a cross-analysis among three European countries—Spain, France, and Italy—to provide insights into the diverse ways in which AI influences professional practices. Through a literature review and semi-structured interviews, the objective is to delineate the challenges of Artificial Intelligence within the framework of the Agenda 2030 program. Subsequently, we will delve into the specificity of AI Literacy in comparison to Information Literacy, a practice already adopted by libraries. Finally, we will analyze the current and prospective role of AI in libraries to propose avenues for implementing concrete actions.

Architecture designing of digital twin in a healthcare unit.

Objectives: This study proposes a novel architecture for designing digital twins in healthcare units. Methods: A systematic research methodology was employed to develop architecture design patterns. In particular, a systematic literature review was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework to answer specific research questions and provide guidelines for designing the architecture. Subsequently, a case study was designed and analyzed at a chemotherapy treatment center for outpatients. Results: System architecture knowledge was distilled from this real-world case study, supplemented by existing software and systems design patterns. A novel five-layer architecture for digital twins in healthcare units was proposed with a focus on the security and privacy of patients' information. Conclusion: The proposed digital twin architecture for healthcare units offers a comprehensive solution that provides modularity, scalability, security, and interoperability. The architecture provides a robust framework for effectively and efficiently managing healthcare environments.

Accelerating Linear Congruential Generators with Carbon Nanotube Field-Effect Transistors

Abstract In the era of technological advancements, safeguarding information privacy has become paramount across sectors like defense, finance, healthcare, and more. At the heart of these security measures lies cryptography, a field that necessitates the efficient processing and secure storage of data. Our project focuses on the optimization of Linear Congruential Generators (LCG), pivotal for cryptographic applications and pseudorandom number generation. Here it has been pioneered the implementation of LCG using Carbon Nanotube Field-Effect Transistor (CNTFET) technology, targeting the reduction of leakage power through the innovative application of sleep techniques. This advanced approach not only embodies a leap towards minimizing energy consumption but also enhances the overall performance and reliability of cryptographic systems. By integrating sleep modes into the CNTFET-based LCG design, our methodology significantly curtails leakage power without compromising the generator’s efficiency or output quality. The successful implementation and synthesis of this design, employing cutting-edge CNTFET technology, underscore the potential for substantial improvements in power efficiency while maintaining high standards of security and randomness essential for cryptographic algorithms.

The Diet Equation: Linking Food, Genetics, and Wellness

Recent research demonstrates that food affects our physiology, and genetic code, influencing health and life span. Our knowledge of diet and wellness has increased significantly, highlighting the connection between our genetic makeup and what we eat in our daily routine. This method changes our conviction about health and offers a modified path to a great lifestyle [1]. Historically, all types of dietary guidelines were based on the study of a large population and generally recommended to everyone. After the involvement of genetic research, the approaches have been different now, a study revealed that everybody processes food and absorbs nutrients differently according to their genetic makeup. For example, some people might metabolize caffeine slowly compared to others, whereas some people have a genetic tendency to lactose intolerance. As per the type of nutritional information, it is stated that nutrients can change the genetic information over the generations. Nutritional genomics also known as nutrigenomics, explores the relationship between the human genome, diet, and health outcomes. Researchers reveal how our body responds to different types of food and nutrients, and also identify the interaction between specific food compounds and genes. Food contains micro and macronutrients and their breakdown activates the genetic switches to regulate the genome. Furthermore, the development of individual genetic testing helps to identify the personal genetic makeup and design their food accordingly, helping to make decisions about the nutrients. The significant increase in cases of diabetes, cardiovascular disease, and obesity has been linked to the high sugar and fat content typical of Western lifestyles. Medical anthropologists and researchers have termed this phenomenon a ‘disease of civilization’. Despite these advancements in the field of nutrigenomics, the integration of genetics and diet is not without challenges. One of the major concerns is the interpretation and application of genetic information. Furthermore, there is a need for more rigorous clinical studies to validate the effect of a personalized based diet on genetic information. Additionally, ethical considerations surrounding genetic data privacy and potential misuse of genetic information are paramount. Assurance that genetic data is handled with confidentiality and that personalized dietary recommendations are based on robust scientific evidence is crucial for maintaining public health. With the advancement in genomics, data science, and biotechnology. We can anticipate a more nuanced understanding of how genetic variations influence nutritional needs and health outcomes. In conclusion, the intersection of genetics, food, and wellness represents a promising frontier in personalized medicine. As research and technology progress, the diet equation will become increasingly sophisticated, paving the way for a future where our diets are as unique as our genetic blueprints.

Analysis on addressing the threats to cloud computing on the basis of security safeguards for sap cloud services

Cloud computing has become an integral part of combination/multi-cloud infrastructures due to its many benefits, including quick deployment, flexibility, cheap costs, and scalability, which have attracted businesses of all sizes. New possibilities and threats in terms of security flaws are cropping up in this field, even if cloud storage provides substantial advantages and inexpensive choices for IT administration and growth. When we talk about safeguarding cloud infrastructure systems, we're referring to a set of rules, regulations, and systematic procedures. This is also known as cloud computing security. The purpose of implementing these security measures is to safeguard cloud-based data, facilitate the enforcement of legislation, ensure the privacy of consumer information, and set standards for encryption in specific devices and applications. Modern cloud computing and security concerns throughout the cloud's many layers are addressed in this study. Within this context, the current study would make a substantial contribution to lowering the frequency of security breaches in cloud computing, paving the way for the continued provision of safe and reliable services. Storage of databases on the cloud is expanding rapidly in the IT industry, including SAP networks. Because enterprises are ultimately responsible for the security of their data, migrating databases to cloud computing environments brings with it a plethora of security risks. To guarantee data integrity, availability, and secrecy, appropriate security measures should be put in place before a company migrates its sensitive data to the cloud. When data is at rest, it is most vulnerable to unauthorized access; when it is in transit, it must be subject to strict supervision.

Decentralized Identity Management for Metaverse-Enhanced Education: A Literature Review

As we transition into the era of Web 3.0, where decentralized information and user privacy are paramount, emerging technologies are reshaping the way in which personal data are managed. This paper focuses on decentralized identity management (DID) in the metaverse, particularly within the education sector, which has rapidly embraced digital tools for e-learning, especially since the COVID-19 pandemic. Technologies such as blockchain, artificial intelligence (AI), and virtual and augmented reality (VR/AR) are increasingly integrated into educational platforms, raising questions about privacy, security, and interoperability. This literature review examines the current landscape of DID in metaverse-based educational applications. Through a systematic methodology, relevant academic papers were identified, filtered, and analyzed based on four key criteria: standardization, interoperability, application scalability, and security/privacy considerations. The paper provides a comparative analysis of these papers to assess the maturity of DID implementations, highlight existing challenges, and suggest future research directions in the intersection of decentralized identity and educational metaverse applications.

Decentralized Stochastic Recursive Gradient Method for Fully Decentralized OPF in Multi-Area Power Systems

This paper addresses the critical challenge of optimizing power flow in multi-area power systems while maintaining information privacy and decentralized control. The main objective is to develop a novel decentralized stochastic recursive gradient (DSRG) method for solving the optimal power flow (OPF) problem in a fully decentralized manner. Unlike traditional centralized approaches, which require extensive data sharing and centralized control, the DSRG method ensures that each area within the power system can make independent decisions based on local information while still achieving global optimization. Numerical simulations are conducted using MATLAB (Version 1.0.0.1) to evaluate the performance of the DSRG method on a 3-area, 9-bus test system. The results demonstrate that the DSRG method converges significantly faster than other decentralized OPF methods, reducing the overall computation time while maintaining cost efficiency and system stability. These findings highlight the DSRG method’s potential to significantly enhance the efficiency and scalability of decentralized OPF in modern power systems.

Blockchain Based Secure File Transfer System with Password Protection

The need of secure file transfer systems is higher nowadays. In order to enhance the security and privacy of private information transferred over the internet, our paper presents a blockchain-based secure file transfer system (BSFTS) with password protection. This system takes advantage of the decentralized and immutable properties of blockchain technology to ensure that every file transfer is Safe and Secure, offering verifiable audit trails that can minimize the threats associated with data tampering and unauthorized access. Through forcing people to use strong, unique passwords for decryption as well as encryption, the combination of password protection further secures files by ensuring that only specified people may access the information. In addition to enhancing data confidentiality, this dual-layer strategy increases defences against possible cyberthreats, including phishing and brute force attacks. Research shows that the blockchain-based secure file transfer system with password protection far exceeds standard file transfer techniques in terms of security and user experience. The results illustrate that password protection and blockchain technology work together to build a robust framework for secure file sharing. For companies trying to enhance their data protection plans in the face of changing security threats in the world of technology, this study provides helpful data

Policing of youth in the hospital

BackgroundEach year millions of children seek care in emergency departments, many of whom are from marginalized and minoritized groups who lack access to primary and preventive care. Law enforcement personnel are also commonly present in pediatric and adult emergency departments serving in a range of roles. Therefore, pediatric emergency departments sit at the nexus of the health system and the legal system for many vulnerable youth and families. ObjectiveHerein, we explore several common specific legal issues surrounding policing of youth in the hospital setting: patient privacy and disclosure of information, questioning and visitation restriction, autonomy and decision making, restraints and use of force, and patient property. MethodsOur team of legal scholars and clinician researchers examined the literature on policing of youth in healthcare settings and patients' legal rights in healthcare settings through searches using PubMed, Westlaw, and Lexis. FindingsThrough rigorous analysis of the medical literature, legal scholarship, and relevant case law, several important themes were identified which present challenges to clinicians caring for vulnerable children. Conclusions and relevancePediatric clinicians, highly trained professionals in the medical and social care of youth and children, are often unaware of legal rules and procedures that guide law enforcement interaction with youth. This lack of knowledge may result in unknowing and unwitting violations of patients' rights while also compromising the quality of health care provided. Therefore, it is imperative that clinicians are educated on their roles and their institutions' roles in safeguarding patients' privacy and autonomy while still promoting effective collaboration with law enforcement.

The Application and Potential Future Development of Artificial Intelligence in Education

With the coming of the era of artificial intelligence, the impact of artificial intelligence technology on basic education has been widely discussed, but there are still many problems and challenges. This paper focuses on the analysis of AI technology enabling basic education and the challenges in the application process. This paper concludes that artificial intelligence helps teachers carry out intelligent teaching and promotes students' personalized learning. But at the same time, AI also brings many challenges and risks, such as how to protect privacy and filter information in data overflow; And how to keep students creative while using AI. Based on this, this paper puts forward the following suggestions: the government should strengthen the investment and optimize the allocation of basic education resources; The government will explore the development of ethical norms and regulatory mechanisms applicable to artificial intelligence in the field of education; Schools to strengthen the training and introduction of teachers; Individual students combine artificial intelligence with real life.

Multi-language Psychological Health Chatbot

Diagnosing and treating mental and psychological health problems has long been a challenge for people and psychologists. This is due to several reasons, one of which is society's view, where people can be treated as abnormal. Therefore, with the development of technology, especially artificial intelligence techniques, researchers began to work on finding different ways for people with psychological problems to ensure their privacy and personal information. In this paper, the design and implementation of a chatbot was reviewed for helping people who suffer from some psychological problems, and to take advice or suggest ways to recover based on a database of books related to this topic. A modified artificial intelligence algorithm was used; the chatbot integrates natural language processing (NLP) algorithms to facilitate smooth and intuitive interactions. Taking into account the inability of some Arabic-speaking users to write or understand the answers in English, as the approved sources are mostly written in English. So the feature of translating questions was added and then replying also in the language that the user understands. After the implementation and testing of the chatbot by a group of people, the accuracy of the results was satisfactory. The accuracy rate is up to 85% and the accuracy of the results depends on the accuracy of the questions.

К вопросу реализации алгоритмов проектирования защищенных сетей передачи данных

Existing approaches to the design of secure data transmission networks (DRN) are often based on guidelines for the design of communication networks in a broad sense, at the moment there are no clear regulations for the design of communication networks in a secure version from the point of view of information security. In the process of advanced design of the SPDS, problems arise in finding effective solutions for the construction of such communication networks and ensuring the information security of the SPDS in terms of information security tools (SIS) in given areas determined by information security measurements, such as the availability, accessibility, secrecy of information circulating in the SPDS. The article proposes algorithms based on the parameters of non-stationary hyper-network models, which make it possible to implement the analysis and synthesis of ZSPD, as well as take into account the initial data on the intended users, services/applications implemented on ZSPD under conditions of external destructive effects (VDV).

A robust audio steganography technique based on image encryption using different chaotic maps

The development of innovative methods for concealing critical data in multimedia files has exploded in information security in recent years. Cryptography and steganography cannot be used alone to protect data; rather, they can be combined and used in a single system. Audio steganography is among the most important information security techniques. It involves the concealment of information within audio signals to achieve covert communication. This paper introduces a comprehensive technique that integrates chaos Henon, Baker, and Arnold maps for image encryption with audio steganography to create a robust and secure audio steganography technique. First, the target image is encrypted using chaotic maps. Then, it is embeded within the high frequencies of the cover audio signal based on the Inverse Short Time Fourier Transform (ISTFT) to be transmitted to the destination through the channel. By integrating both encryption and concealment techniques, the cover audio signal quality can be preserved. Moreover, the hidden image security and robustness are improved, making the technique resistant to many types of attacks. The simulation results confirm that the suggested technique is robust in the presence of attacks. It achieves a distinct perceptual quality with an appreciated peak signal-to-noise ratio (PSNR) of 91.2 dB and a Mean Square Error (MSE) of 7.5 × 10–10. The randomness of the resulting encrypted image has successfully passed the National Institute of Standards and Technology (NIST) statistical test suite.