An efficient and secure data auditing scheme based on fog-to-cloud computing for Internet of things scenarios by Jun-Feng Tian, Hao-Ning Wang

“…With the widespread use of fog-to-cloud computing–based Internet of things devices, how to ensure the integrity of the data uploaded to the cloud has become one of the most important security issues. …”
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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

“…However, trajectory data are often mutilated because of personal privacy and hardware limitations, i.e., we usually can only obtain partial trajectory information. …”
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Harnessing multi-source data for AI-driven oncology insights: Productivity, trend, and sentiment analysis by Wissal EL HABTI, Abdellah AZMANI

“…The most prominent article emphasized the Explainability of AI methods (XAI) with a profound discussion of their potential implications and privacy in data fusion contexts. Current trends involve the utilization of supervised learning methods such as CNN, Bayesian networks, and extreme learning machines for various cancers, particularly breast, lung, brain, and skin cancer. …”
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Mapping the landscape of government data breaches: A bibliometric analysis of literature from 2006 to 2023 by Supardi Hamid, Mohammad Nurul Huda

“…Data breaches in the government sector are severe threats to cybersecurity and illegal acts that flagrantly violate security and privacy laws. …”
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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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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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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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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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Sustainability of the Digital Economy in Indonesia: Opportunities, Challenges and Future Development by Nina Farliana, Indri Murniawaty, Hanif Hardianto

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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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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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Challenges and strategies in building a foundational digital health data integration ecosystem: a systematic review and thematic synthesis by Radha Ambalavanan, R Sterling Snead, Julia Marczika, Gideon Towett, Alex Malioukis, Mercy Mbogori-Kairichi

“…A thematic synthesis approach was used to categorize findings into three primary themes: interoperability, PCC, and genomic data integration.ResultsA total of 161 studies were included. …”
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Blockchain-Based Modified AES with Chaotic Random Key Generation for Secured E-Medical Data Sharing by Vinothkumar.M, R. Saravana Ram

“…Besides, a Modified Digest hashing algorithm is also used with M-AES for feeding the encrypted text and hash into data blocks. …”
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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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Edge-FLGuard: A Federated Learning Framework for Real-Time Anomaly Detection in 5G-Enabled IoT Ecosystems by Manuel J. C. S. Reis

“…The rapid convergence of 5G networks and Internet of Things (IoT) technologies has unlocked unprecedented connectivity and responsiveness across smart environments—but has also amplified cybersecurity risks due to device heterogeneity, data privacy concerns, and distributed attack surfaces. …”
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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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