231 Results Found

This study analyzed how Korea’s quarantine policy manages personal information to prevent and control COVID-19. Korea effectively halted the spread of COVID-19 through epidemiological investigations and cell-broadcast systems. In this process,...

With the advent of the pandemic (e.g., novel corona virus disease 2019 (COVID-19)), a tremendous amount of data about individuals are collected by the health authorities on daily basis for curbing the disease’s spread. The individuals’ data collectio...

We propose a novel continual self-supervised learning (CSSL) framework for simultaneously learning diverse features from multi-window-obtained chest computed tomography (CT) images and ensuring data privacy. Achieving a robust and highly generalizabl...

During medical treatment, personal privacy is involved and must be protected. Healthcare institutions have to keep medical images or health information secret unless they have permission from the data owner to disclose them. Reversible data hiding (R...

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This study examines how Chinese and Western news media covered artificial intelligence (AI) privacy issues in higher education from 2019 to 2024. News articles were retrieved from Nexis Uni. First, non-negative matrix factorization (NMF) was employed...

There has been a paradigm shift in global communications since the death many years ago of prominent Canadians Marshall McLuhan and Pierre Elliott Trudeau. The correspondence between the two friends, from 1968 to 1980, presciently touched on our cont...

The integration of automation and shared mobility services would significantly affect transportation demand, especially mode choice. However, little is known about how attitudes, travel attributes, and demographic factors affect the modal shift to sh...

Satellite image recognition increasingly relies on data collected by geographically distributed institutions, but centralizing geospatial imagery is often infeasible due to policy and privacy constraints. Federated learning enables collaborative trai...

This work proposes a new architectural approach to enhance the security, privacy, and scalability of VANETs through threshold key management and Privacy Enhancing Technologies (PETs), such as homomorphic encryption and secure multiparty computation,...

Data democratization (DD) is a new concept rapidly becoming a game-changer, enabling companies to innovate and maintain a competitive edge in a data-driven world. This paper explores the evolution of data accessibility, from the early days of manual...

The paradigm-shifting developments of cryptography and information theory have focused on the privacy of data-sharing systems, such as epidemiological studies, where agencies are collecting far more personal data than they need, causing intrusions on...

Currently, the computational power present in the sensors forming a wireless sensor network (WSN) allows for implementing most of the data processing and analysis directly on the sensors in a decentralized way. This shift in paradigm introduces a shi...

With the development of 6G communication technology, Space–Air–Ground Integrated Networks (SAGINs) have become critical infrastructure for global intelligent collaborative computing. However, federated learning deployment in SAGINs faces...

Deep learning techniques for medical image analysis often encounter domain shifts between source and target data. Most existing approaches focus on unsupervised domain adaptation (UDA). However, in practical applications, many source domain data are...

Federated learning (FL) is creating a paradigm shift in machine learning by directing the focus of model training to where the data actually exist. Instead of drawing all data into a central location, which raises concerns about privacy, costs, and d...

The whole world is quickly transforming into an information world with the setup of smart cities, among other things. Information and other forms of privacy are therefore at risk due to the growing intelligence of hackers. Therefore, to enhance the s...

Integrating Artificial Intelligence (AI) in healthcare represents a transformative shift with substantial potential for enhancing patient care. This paper critically examines this integration, confronting significant ethical, legal, and technological...

Artificial intelligence (AI) is rapidly shifting from experimental pilots to mainstream clinical infrastructure, redefining how evidence, accountability, and ethics intersect in healthcare. This narrative review integrates insights from peer-reviewed...

With the growing popularity of cloud computing, it is convenient for data owners to outsource their data to a cloud server. By utilizing the massive storage and computational resources in cloud, data owners can also provide a platform for users to ma...

In modern industrial environments, camera-based monitoring is essential for workflow optimization, safety, and process control, yet it raises significant privacy concerns when people are recorded. Realistic full-body anonymization offers a potential...

Mobility-as-a-Service (MaaS) represents a transformative shift in transportation, enabling users to plan, book, and pay for diverse mobility services via a unified digital platform. While previous research has explored factors influencing MaaS adopti...

The EU’s General Data Protection Regulation (GDPR) has recently come into effect and insofar as Internet of Things (IoT) applications touch EU citizens or their data, developers are obliged to exercise due diligence and ensure they undertake Da...

The current shift towards digital transactions emphasizes the need for robust Qualified Electronic Signature (QES) frameworks that safeguard integrity and privacy. Having the potential to become the leading type of adopted QES, the main challenge tha...

Political communication has been extensively studied through both the broader context of societal and political systems, as well as through the lens of mediatization, which emphasizes the intersection of political and media logics. Within this framew...

The advances in information and communication technology are consistently beneficial for the healthcare sector. A trend in the healthcare sector is the progressive shift in how data are acquired and the storage of such data in different facilities, s...

Privacy amplification is an indispensable procedure for key generation in the quantum key distribution system and the physical layer key distribution system. In this paper, we propose a high-speed privacy amplification algorithm that saves hardware m...

Security and privacy of patients’ data is a major concern in the healthcare industry. In this paper, we propose a system that activates robust security and privacy of patients’ medical records as well as enables interoperability and data exchange bet...

Medical image segmentation faces significant challenges due to domain shift between different clinical centers and data privacy restrictions. Current source-free domain adaptation methods for medical images suffer from three critical limitations, inc...

Background: Neuroimaging-based diagnostic approaches are of critical importance for the accurate diagnosis and treatment of major depressive disorder (MDD). However, multisite neuroimaging data often exhibit substantial heterogeneity in terms of scan...

Mobile payment platforms not only streamline users’ financial transactions but also encourage their participation in investment activities and additional services. To deliver personalized financial services, it is essential to collect users&rsq...

Objectives: To investigate the current state of affective computing in healthcare, focusing on its application contexts, algorithmic trends, and the technical–ethical duality involving data privacy and security. Methods and Results: A systemati...

Anonymous credential (AC) systems are privacy-preserving authentication mech-anisms that allow users to prove that they have valid credentials anonymously. These systems provide a powerful tool for several practical applications, such as anonymous pa...

Current object detection methods deployed in closed-circuit television (CCTV) systems experience substantial performance degradation due to domain gaps between training datasets and real-world environments. At the same time, increasing privacy concer...

This paper presents a qualitative study of the experience of students of the shift from face-to-face learning to online learning during the COVID-19 lockdown in Norway. Detailed inputs were collected from 200 university students enrolled in a bachelo...

This paper examines the evolution of urban vitality measurement, emphasizing the transformative impact of big data and Internet of Things (IoT) technologies. Traditionally assessed through direct observations and surveys, urban vitality measurement h...

In today’s volatile supply chain (SC) environment, competition has shifted beyond individual companies to the entire SC ecosystem. Reducing overall SC costs is crucial for success and benefits all participants. One effective approach to achieve...

With the rapid development of vehicular network technology, data sharing and collaborative training among vehicles have become key to enhancing the efficiency of intelligent transportation systems. However, the heterogeneity of data and potential Byz...

Integrating deep learning (DL) with the Internet of Medical Things (IoMT) is a paradigm shift in modern healthcare, offering enormous opportunities for patient care, diagnostics, and treatment. Implementing DL with IoMT has the potential to deliver b...

Deep learning has undergone significant progress for machinery fault diagnosis in the Industrial Internet of Things; however, it requires a substantial amount of labeled data. The lack of sufficient fault samples in practical applications remains a c...

Despite advances in biomedical treatments, women living with HIV (WLH) who experience homelessness and housing instability suffer suboptimal HIV outcomes, even when linked to treatment. The purpose of this study was to explore experiences of housing...

Robust reversible watermarking in an encrypted domain is a technique that preserves privacy and protects copyright for multimedia transmission in the cloud. In general, most models of buildings and medical organs are constructed by three-dimensional...

This study addresses the challenge of evaluating artificial intelligence (AI) systems across heterogeneous regulatory frameworks. Although the NIST AI RMF, EU AI Act, and ISO/IEC 23894/42001 define important governance requirements, they do not provi...

Fully homomorphic encryption (FHE) offers a promising solution for privacy-preserving machine learning by enabling arbitrary computations on encrypted data. However, the efficient evaluation of non-linear functions—such as the ReLU activation f...

The evolution of Patient-Generated Health Data (PGHD) represents a major shift in healthcare, fueled by technological progress. The advent of PGHD, with technologies such as wearable devices and home monitoring systems, extends data collection beyond...

The Internet of Things (IoT) is a leading trend with numerous opportunities accompanied by advantages as well as disadvantages. Parallel with IoT development, significant privacy and personal data protection challenges are also growing. In this regar...

Background/Objectives: Accurate brain tumor segmentation from MRI is crucial for diagnosis but faces challenges like domain shifts across medical centers, data privacy constraints, and high annotation costs. While source-free active domain adaptation...

As the interest in social and assistive support robots (SASRs) grows, a review of 17 systematic reviews was conducted to assess their use in healthcare, emotional well-being, and therapy for diverse populations, including older adults, children, and...

A bathroom has higher probability of accidents than other rooms due to a slippery floor and temperature change. Because of high privacy and humidity, we face difficulties in monitoring inside a bathroom using traditional healthcare methods based on c...

To provide diverse in-home services like elderly care, versatile activity recognition technology is essential. Radio-based methods, including WiFi CSI, RFID, and backscatter communication, are preferred due to their minimal privacy intrusion, reduced...