Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response by Yan Yan, Pengbin Yan, Adnan Mahmood, Yang Zhang, Quan Z. Sheng

“…The widespread use of spatial location-based services not only provides considerable convenience, but also exposes the downsides of location privacy leakage. …”
Get full text

Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Federated Learning (FL) offers an encouraging solution to address these challenges by providing a privacy-preserving solution for investigating and detecting cyberattacks in IoT systems without negotiating data privacy. …”
Get full text

Ethical and privacy challenges of integrating generative AI into EHR systems in Tanzania: A scoping review with a policy perspective by Augustino Mwogosi

“…Results The review identified six key ethical and privacy challenges associated with generative AI in EHR systems: data privacy and security risks, algorithmic bias and fairness concerns, transparency and accountability issues, consent and autonomy challenges, human oversight gaps and risks of data re-identification. …”
Get full text

Enhancing accuracy through ensemble based machine learning for intrusion detection and privacy preservation over the network of smart cities by Mudita Uppal, Yonis Gulzar, Deepali Gupta, Jayant Uppal, Mukesh Kumar, Shilpa Saini

Get full text

Smart Grid Intrusion Detection for IEC 60870-5-104 With Feature Optimization, Privacy Protection, and Honeypot-Firewall Integration by Pedamallu Sai Mrudula, Rayappa David Amar Raj, Archana Pallakonda, Yanamala Rama Muni Reddy, K. Krishna Prakasha, V. Anandkumar

“…Furthermore, the proposed framework includes a federated learning-based scheme that utilizes differential privacy and homomorphic encryption to ensure the privacy and integrity of the data to enhance model interpretability and efficiency with feature ranking to provide insights into attack patterns and anomaly characteristics. …”
Get full text

Privacy-Preserving Glycemic Management in Type 1 Diabetes: Development and Validation of a Multiobjective Federated Reinforcement Learning Framework by Fatemeh Sarani Rad, Juan Li

“…Furthermore, these approaches typically rely on centralized data processing, which raises privacy concerns due to the sensitive nature of health care data. …”
Get full text

A federated learning-based privacy-preserving image processing framework for brain tumor detection from CT scans by Abdullah Al-Saleh, Ghanshyam G. Tejani, Shailendra Mishra, Sunil Kumar Sharma, Seyed Jalaleddin Mousavirad

“…Because traditional deep learning models store all their data together, they raise questions about privacy, complying with regulations and the different types of data used by various institutions. …”
Get full text

Multimodal Video Analysis for Crowd Anomaly Detection Using Open Access Tourism Cameras by Alejandro Dionis-Ros, Joan Vila-Francés, Rafael Magdalena-Benedito, Fernando Mateo, Antonio J. Serrano-López

Get full text

A novel end-to-end privacy preserving deep Aquila feed forward networks on healthcare 4.0 environment by Ponugoti Kalpana, Sunitha Tappari, L. Smitha, Dasari Madhavi, K. Naresh, Maddala Vijayalakshmi

“…Though sensor-driven devices have largely eased everyday lives, these healthcare systems have been suffering from various security breaches and data privacy problems. This evokes a need for designing intelligent systems to eradicate data breaches and privacy problems. …”
Get full text

Effect of Workshop Training on Nursing Students’ Knowledge and Attitude Regarding Children’s Privacy Protection: A Quasi-experimental Study by Fatemeh Azimi, Fariba Asgari, Yasaman Yaghobi, Saman Maroufizadeh, Morteza Rahbar Taramsari

“…Data analysis was performed by using descriptive (Mean±SD, frequency, percentage) and inferential statistics (Pearson correlation test and analysis of covariance). …”
Get full text

A Decision Cloud Ranking Approach Based on Privacy and Security in Blockchain E-Health Industry 4.0 Systems by Sarah Qahtan, Khaironi Yatim, Mohd Hafeez Osman, Hazura Zulzalil, Muhammad Luqman Mahamad Zakaria

“…Second, the weights of each privacy and security property are calculated using the SFS-FWZIC method. …”
Get full text

Enhancing Cybersecurity and Privacy Protection for Cloud Computing-Assisted Vehicular Network of Autonomous Electric Vehicles: Applications of Machine Learning by Tiansheng Yang, Ruikai Sun, Rajkumar Singh Rathore, Imran Baig

“…However, more connected and engaged nodes also increase the system’s vulnerability to cybersecurity and privacy breaches. Various security and privacy challenges in vehicular cloud computing and its variants (VEC, VFC) can be efficiently tackled using machine learning (ML). …”
Get full text

Network Attack Detection for Business Safety by Fadia Abduljabbar Saeed, Ghalia Nassreddine, Joumana Younis

Get full text

The Use of Artificial Intelligence in Combating Financial Crimes and Money Laundering in International Trade A Data-Driven Analysis (2010–2024) by Balouz Mohamed

Get full text

Psychiatrists’ and trainees’ knowledge, perception, and readiness for integration of artificial intelligence in mental health care in Nigeria by Olatunji Alao Abiodun, Peter Omoniyi Ajiboye, Mumeen Olaitan Salihu, Dauda Sulyman, Adesanmi Akinsulore, Okwudili Obayi, Hassan Bala Salihu

Get full text

Deep Learning-Based Real Time Human Detection System Using LiDAR Data for Smart Healthcare Monitoring by Kalashtari Niloofar, Huhs Niklas, Kraitl Jens, Hornberger Christoph, Simanski Olaf

“…By training a YOLOv5 deep learning model using transfer learning, a method for accurate human detection and tracking within rooms using data collected from a digital LiDAR sensor was used. …”
Get full text

The Impact of Artificial Intelligence on the Future Business World by Hebah Y. AlQato

“…In order to assist businesses better understand their consumers' requirements and preferences, AI is being used to examine customer data and generate insights. …”
Get full text

Determinants of Childbirth Choice in Rural Senegal: Mixed-Methods Analysis Using Data from the Niakhar Demographic Surveillance System by Pape Latyr Faye

“…Materials and methods: The study used a mixed-methods approach. Data from women who gave birth in the Niakhar observatory area between 1983 and 2020 were used, and chi-square tests and qualitative analyses were performed. …”
Get full text

FedDBO: A Novel Federated Learning Approach for Communication Cost and Data Heterogeneity Using Dung Beetle Optimizer by Dongyan Wang, Limin Chen, Xiaotong Lu, Yidi Wang, Yue Shen, Jingjing Xu

“…After aggregating the model parameters sent by clients, the server performs a second iterative training on the aggregated model using its own metadata, thereby reducing data heterogeneity and improving model performance. …”
Get full text

Comparative Analysis of RAG-Based Open-Source LLMs for Indonesian Banking Customer Service Optimization Using Simulated Data by Hendra Lijaya, Patricia Ho, Handri Santoso

“…These findings underscore the potential of locally operated open-source LLMs for banking applications, ensuring privacy and regulatory compliance. However, limitations include reliance on synthetic data, a narrow question set, and lack of user diversity. …”
Get full text