Data Anonymization and Privacy Preservation in Healthcare Systems by Datta Krishnasheesh, Gupta Himanshu

Get full text

Cloud data anonymous assured deletion approach based on blockchain by Shuangxing WANG, Jintang LUO, Lisha SHUAI, Jiamin ZHANG, Min ZHANG, Xiaolong YANG

Get full text

Cloud data anonymous assured deletion approach based on blockchain by Shuangxing WANG, Jintang LUO, Lisha SHUAI, Jiamin ZHANG, Min ZHANG, Xiaolong YANG

Get full text

Balancing Privacy and Accuracy: Exploring the Impact of Data Anonymization on Deep Learning Models in Computer Vision by Jun Ha Lee, Su Jeong You

Get full text

A hybrid rule-based NLP and machine learning approach for PII detection and anonymization in financial documents by Kushagra Mishra, Harsh Pagare, Kanhaiya Sharma

Subjects: Get full text

Automated redaction of names in adverse event reports using transformer-based neural networks by Eva-Lisa Meldau, Shachi Bista, Carlos Melgarejo-González, G. Niklas Norén

Subjects: Get full text

A Combined Approach of Heat Map Confusion and Local Differential Privacy for the Anonymization of Mobility Data by Christian Dürr, Gabriele S. Gühring

Subjects: “…mobility data anonymization…”
Get full text

Future on Wheels: Safeguarding Privacy in Tomorrow’s Connected Vehicles-FUTURE-SP by Faycal Znidi, Mohamed Morsy, Heena Rathore

Subjects: Get full text

(<italic>r, k, &#x03B5;</italic>)-Anonymization: Privacy-Preserving Data Publishing Algorithm Based on Multi-Dimensional Outlier Detection, <italic>k</italic>-Anonymity, and <itali... by Burak Cem Kara, Can Eyupoglu, Oktay Karakus

Subjects: Get full text

Meta-learning approach for variational autoencoder hyperparameter tuning by Michele Berti, Matheus Camilo da Silva, Sebastiano Saccani, Sylvio Barbon Junior

“…Synthetic data generation is a promising alternative to traditional data anonymization, with Variational Autoencoders (VAEs) excelling at generating high-quality synthetic tabular datasets. …”
Get full text

Diagnosis of rheumatic and autoimmune diseases datasetDataverse by Mohammed Fadhil Mahdi, Arezoo Jahani, Dhafar Hamed Abd

“…Patient privacy is ensured through data anonymization. The dataset includes 14 features in seven classes, aiding the development of machine learning models for the early and accurate diagnosis of rheumatic and autoimmune diseases. …”
Get full text

Contextual integrity in Africa's plural-legal contexts: Fintech, privacy, and informational norms in Ghana by Aisha PL Kadiri, Emmanuel Frimpong Boamah

“…Our findings illuminate a nuanced and contextually rooted understanding of privacy, focusing on the complementarities and tensions around data anonymization for privacy; the multiplicity of information spheres that result in a complicated terrain of privacy breaches; and the individuality, mutuality, and collectivity of privacy harms and remedies thereof. …”
Get full text

Evaluating the Impact of Face Anonymization Methods on Computer Vision Tasks: A Trade-Off Between Privacy and Utility by Roland Stenger, Steffen Busse, Jonas Sander, Thomas Eisenbarth, Sebastian Fudickar

“…Data anonymization is an essential prerequisite that enables data sharing in a privacy-preserving manner. …”
Get full text

Editorial by Christian Gütl

“…These contributions, together with the generous support of the KOALA initiative, maintain the quality of our journal.In the sixth regular issue, I am very pleased to present the following 4 accepted articles: Michele Berti, Matheus Camilo da Silva, Sebastiano Saccani, and Sylvio Barbon from Italy focus their research on synthetic data generation as an alternative to traditional data anonymization based on variational autoencoders to generate high-quality synthetic tabular datasets.Roger Vieira and Kleinner Farias from Brazil introduce in their research CognIDE, a tool-supported methodology that aims to seamlessly integrate psychophysiological data linked to cognitive indicators into VS Code by offering actionable contextual cues alongside dynamic source code.Pedro Henrique Dias Valle and Elisa Yumi Nakagawa from Brazil discuss in their research a catalog of the main interoperability architectural solutions for addressing the four levels of interoperability - namely technical, syntactic, semantic, and organizational &amp;ndash; for solving interoperability issues in software systems by analyzing 65 studies from the scientific literature.Ji Woong Yoo, Kyoung Jun Lee and Arum Park from the Republic of Korea explore the potential of deep learning techniques - Long Short-Term Memory (LSTM) algorithm and Word2Vec model &amp;ndash; for cleansing malicious comments from users, and enhancing the ethical nature of AI systems.Enjoy Reading!…”
Get full text

Patients’, parents’, and survivors’ perspective about AI applications in pediatric oncology by Hyseni Bocolli Albina, Schneider Carina, Bastos Pais Teresa, Willi Michaela, Brunmair Mattias

“…To delve deeper into the survey findings, discussions were held with a diverse focus group, including four parents of childhood cancer former patients (survivors), three childhood cancer survivors, and one bereaved parent, each representing different backgrounds, age groups, and countries.Insights and outcomes of this study produced a report for guiding the multi-stakeholder board of the project when defining the governance structures reg. data sharing, ownership, protection, access and usage.Perspective of parents, patients and survivors of pediatric cancer regarding AI applications in Pediatric Oncology focused in six areas of interest including: data anonymization and data protection, data ownership, data withdrawal, ethical concerns of use of data, data types and, additionally, informed consents. …”
Get full text

Dataset of anonymized discharge summaries of sepsis patients from a Brazilian tertiary hospital for NLP applications.Dataverse by Rildo Pinto da Silva, Antonio Pazin-Filho

“…The main reason for this is data sensitivity, which dictates the need for accurate data anonymization. This article describes a new dataset compiled to help bridge the gap in publicly available information in this area. …”
Get full text

Automated pipeline for linear and volumetric assessment of facial swelling after third molar surgery by Selene Barone, Paolo Zaffino, Marianna Salviati, Michela Destito, Alessandro Antonelli, Francesco Bennardo, Lucia Cevidanes, Maria Francesca Spadea, Amerigo Giudice

“…The open-source software 3DSlicer facilitated automated analysis, including data anonymization, orientation, surface registration, qualitative comparisons, linear measurements, and volumetric quantification. …”
Get full text

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review by ShiYing Shen, Wenhao Qi, Jianwen Zeng, Sixie Li, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Yankai Shi, Jiani Yao, Bingsheng Wang, Xiajing Lou, Simin Gu, Pan Li, Jinghua Wang, Guowei Jiang, Shihua Cao

“…We identified critical limitations, including small samples (32/42, 76% with N<100), short monitoring periods (19/42, 45% <7 days), scarce external validation (1/42, 2%), and limited reporting on data anonymization (6/42, 14%). ConclusionsWhile passive sensing and ML demonstrate promising accuracy (eg, convolutional neural network–long short-term memory achieving 92.16% in anxiety detection), the evidence remains constrained by three key limitations: (1) methodological heterogeneity (32/42, 76% single-device studies; 19/42, 45% with <7-day monitoring), (2) high risk of bias from small samples (median 60.5, IQR 54-99 participants) and scarce external validation (1/42, 2%), and (3) ethical gaps (only 6/42, 14% addressing anonymization). …”
Get full text

Google's Project Nightingale highlights the necessity of data science ethics review by Christophe Olivier Schneble, Bernice Simone Elger, David Martin Shaw

“…As the Wall Street Journal had already reported 3 days earlier, and as the whistleblower confirmed, neither was the data anonymized when transmitted from Ascension nor were patients or their doctors notified, let alone asked for consent to sharing their data with Google (Copeland, 2019; Pilkington, 2019). …”
Get full text

Smart framework for industrial IoT and cloud computing network intrusion detection using a ConvLSTM-based deep learning model by Ala' Abdulmajid Eshmawi, Asma Aldrees, Raed Alharthi

“…This study examines data anonymity, security, and preservation in the Edge IIoT environment, focusing on cloud computing and cyber-physical systems. …”
Get full text