F-DATA: A Fugaku Workload Dataset for Job-centric Predictive Modelling in HPC Systems by Francesco Antici, Andrea Bartolini, Jens Domke, Zeynep Kiziltan, Keiji Yamamoto

“…The encoding is based on a Natural Language Processing model and retains sensitive but useful job information for prediction purposes without violating privacy concerns.…”
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CGFL: A Robust Federated Learning Approach for Intrusion Detection Systems Based on Data Generation by Shu Feng, Luhan Gao, Leyi Shi

“…It employs a data generator that integrates artificially generated data with the existing data from local clients by employing label correction and data generation techniques. …”
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Next Arrival and Destination Prediction via Spatiotemporal Embedding with Urban Geography and Human Mobility Data by Pengjiang Li, Zaitian Wang, Xinhao Zhang, Pengfei Wang, Kunpeng Liu

“…In this paper, we develop an embedding method to predict the next arrival using the origin–destination (O-D) pair trajectory information and point of interest (POI) data. …”
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Evolution, topics and relevant research methodologies in business intelligence and data analysis in the academic management of higher education institutions. A literature review by M. Correa-Peralta, J. Vinueza-Martínez, L. Castillo-Heredia

“…In the digital era, Business Intelligence (BI) and data analytics have become essential for optimizing academic management in higher education institutions. …”
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How machine learning on real world clinical data improves adverse event recording for endoscopy by Stefan Wittlinger, Isabella C. Wiest, Mahboubeh Jannesari Ladani, Jakob Nikolas Kather, Matthias P. Ebert, Fabian Siegel, Sebastian Belle

“…This study evaluates a machine learning-based approach for systematically detecting endoscopic adverse events from real-world clinical metadata, including structured hospital data such as ICD-codes and procedure timings. Using a random forest classifier detecting adverse events perforation, bleeding, and readmission, we analysed 2490 inpatient cases, achieving significant improvements over baseline prediction accuracy. …”
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Unraveling the role of data sharing in open finance diffusion: an evolutionary game approach on complex networks by Dongqing Chen, Chaoqun Ma, Liwei Zhang, Lijie Li

“…In this study, we develop a diffusion model using evolutionary game theory on complex networks to explore how data sharing influences lenders’ micro-level decision-making and promotes the macro-level diffusion of open finance. …”
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Boosting EEG and ECG Classification with Synthetic Biophysical Data Generated via Generative Adversarial Networks by Archana Venugopal, Diego Resende Faria

“…By addressing the challenges of limited biophysical data, including privacy concerns and restricted volunteer availability, our model generates realistic synthetic waveforms learned from real data. …”
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A Robust Image Encryption Protocol for Secure Data Sharing in Brain Computer Interface Applications by Sunil Prajapat, Pankaj Kumar, Kashish Chaudhary, Kranti Kumar, Gyanendra Kumar, Ali Kashif Bashir

“…However, the susceptibility of BCI data to tampering during transmission underscores the critical need for robust security and privacy measures. …”
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Exploring assessment methods used by Grade Four English First Additional Language Teachers by Kofi Nkonkonya Mpuangnan, Gladys Phumzile Mngomezulu, Samantha Govender

“…The researchers opted for a thematic analysis approach, allowing for a thorough examination of the data while respecting the privacy and confidentiality of the participants. …”
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Artificial intelligence methods used in various aquaculture applications: A systematic literature review by Thurein Aung, Rafiza Abdul Razak, Adibi Rahiman Bin Md Nor

“…However, the review also uncovered substantial challenges that will continue limiting widespread adoption, including restricted access to representative data, prohibitive expenses, technical complexities, lack of social acceptance, and data privacy and security concerns. …”
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Analysis of the Obstacles to Ethical Use of Artificial Intelligence by Abbas Shoul, Mohammad Amini, Fatemeh Arabpour

“…Results: The results show that among the 6 identified barriers (lack of accountability, lack of transparency, lack of legal regulations, possibility of bias and discrimination, violation of data privacy, and violation of social justice and livelihood of individuals), the barrier of lack of transparency, followed by the lack of legal regulations, are considered to be the most important and influential barriers to the ethical use of AI. …”
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An Adaptive Window Size Selection Method for Differentially Private Data Publishing over Infinite Trajectory Stream by Geonhyoung Jo, Kangsoo Jung, Seog Park

“…Differential privacy techniques are being used as a de facto standard to prevent such privacy violation caused by data analysis. …”
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Can open source large language models be used for tumor documentation in Germany?—An evaluation on urological doctors’ notes by Stefan Lenz, Arsenij Ustjanzew, Marco Jeray, Meike Ressing, Torsten Panholzer

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Factors Affecting Personal Information Sharing: Small-Scale Sample Analysis on Social Media by Belia Rida Syifa Fauzia, Lukman Yudokusumo, Yova Ruldeviyani

“…These findings indicated that users’ trust, awareness, privacy concerns, and behavioral intentions significantly and positively influence the tendency to share personal data on social media platforms. …”
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The Use of Blockchain Technology in the Food Traceability System by Cecilia Rasetto

“…To enhance clarity, the paper examines a use case related to agricultural inputs, commodities, and products in the cereals sector to illustrate the application of data collection devices and the role of blockchain technology in data validation, storage, security, and transmission. …”
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Sustainability of the Digital Economy in Indonesia: Opportunities, Challenges and Future Development by Nina Farliana, Indri Murniawaty, Hanif Hardianto

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Large language models generating synthetic clinical datasets: a feasibility and comparative analysis with real-world perioperative data by Austin A. Barr, Joshua Quan, Eddie Guo, Emre Sezgin, Emre Sezgin

“…Synthetic data offers a promising solution to preserve privacy while enabling broader data access. …”
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Digital evidence and its use for criminal proceedings by Jakub Matis

“…By examining these aspects, the paper contributes to a deeper understanding of how digital evidence is utilized in criminal investigations and legal proceedings, advocating for legislative updates to address the growing importance of digital data in modern criminal cases. Furthermore, it underscores the need for careful consideration of privacy rights and proportionality when dealing with personal information obtained from digital devices and online platforms. …”
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Secure federated distillation GAN for CIDS in industrial CPS by Junwei LIANG, Geng YANG, Maode MA, Sadiq Muhammad

“…Aiming at the data island problem caused by the imperativeness of confidentiality of sensitive information, a secure and collaborative intrusion detection system (CIDS) for industrial cyber physical systems (CPS) was proposed, called PFD-GAN.Specifically, a novel semi-supervised intrusion detection model was firstly developed by improving external classifier-generative adversarial network (EC-GAN) with Wasserstein distance and label condition, to strengthen the classification performance through the use of synthetic data.Furthermore, local differential privacy (LDP) technology was incorporated into the training process of developed EC-GAN to prevent sensitive information leakage and ensure privacy and security in collaboration.Moreover, a decentralized federated distillation (DFD)-based collaboration was designed, allowing multiple industrial CPS to collectively build a comprehensive intrusion detection system (IDS) to recognize the threats under the entire cyber systems without sharing a uniform template model.Experimental evaluation and theory analysis demonstrate that the proposed PFD-GAN is secure from the threats of privacy leaking and highly effective in detecting various types of attacks on industrial CPS.…”
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Cybersecurity Anomaly Detection: AI and Ethereum Blockchain for a Secure and Tamperproof IoHT Data Management by Oluwaseun Priscilla Olawale, Sahar Ebadinezhad

“…Since medical Information Technology (IT) is evolving and data privacy is a major concern with sensors generally, in healthcare IoT. …”
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