Enabling Secure and Scalable GDPR-Compliant Blockchain-Based e-KYC With Efficient Redaction by Somchart Fugkeaw, Surabordin Sungchai, Supawit Nakprame, Piphattra Sreekongpan

“…To address these gaps, we propose a novel blockchain-based e-KYC framework that is GDPR-compliant, privacy-preserving, and highly scalable. Our solution introduces three key innovations: 1) ZK-Rollup-based authentication integrated with sharded blockchain architecture, enabling off-chain proof batching and distributed verification across shards for high-throughput, low-latency validation; 2) adaptive proxy re-encryption to support secure and dynamic customer data portability between host and requesting FIs; and 3) an optimized redactable blockchain protocol using off-chain Chameleon Hash collision generation and threshold cryptography-based key rotation to enable efficient, secure, and verifiable data updates in compliance with GDPR. …”
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The potential of machine learning in diagnosing neurological and psychiatric diseases: a review by Claudia Ricetti, Luca Carrara, Davide La Torre

“…However, certain challenges persist, including concerns about data quality, patient privacy and the ethical implications of algorithmic decisions. …”
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Generalization challenges in video deepfake detection: methods, obstacles, and technological advances by LI Junjie, WANG Jianzong, ZHANG Xulong, QU Xiaoyang

“…However, its widespread use and decreasing costs pose serious threats to personal privacy and social trust. …”
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Personalized Mobile Health for Elderly Home Care: A Systematic Review of Benefits and Challenges by Shahrbanoo Pahlevanynejad, Sharareh R. Niakan Kalhori, Meysam Rahmani Katigari, Rahil Hosseini Eshpala

“…The results indicated that 25% of the challenges were related to privacy, cybersecurity, and data ownership (10%), technology (7.5%), and implementation (7.5%). …”
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Reinventing Cybersecurity Internships During the COVID-19 Pandemic by Lori L. Sussman

“…The goal is to reach out to underrepresented populations who may use Federal Work-Study (FWS) or grant sponsored internships to participate. …”
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Generalization challenges in video deepfake detection: methods, obstacles, and technological advances by LI Junjie, WANG Jianzong, ZHANG Xulong, QU Xiaoyang

“…However, its widespread use and decreasing costs pose serious threats to personal privacy and social trust. …”
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Dual defense: Combining preemptive exclusion of members and knowledge distillation to mitigate membership inference attacks by Jun Niu, Peng Liu, Chunhui Huang, Yangming Zhang, Moxuan Zeng, Kuo Shen, Yangzhong Wang, Suyu An, Yulong Shen, Xiaohong Jiang, Jianfeng Ma, He Wang, Gaofei Wu, Anmin Fu, Chunjie Cao, Xiaoyan Zhu, Yuqing Zhang

“…Membership inference (MI) attacks threaten user privacy through determining if a given data example has been used to train a target model. …”
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Making temporary homes by Marjolein Overtoom

“…The interviews were analysed with Interpretative Phenomenological Analysis, and the visual data (photos made by the interviewees and sometimes the researcher, and drawings made by the researcher) was used to place the content of the interviews in a physical context. …”
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Contrastive Learning Algorithm for Low-Resource Cryptographic Attack Event Detection by Peng Luo, Rangjia Cai, Yuanbo Guo

“…The widespread use of the internet has led to frequent cryptographic attack event incidents, which pose various risks, including the leakage of personal information, privacy data, identity theft, and potential legal liabilities. …”
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Optimising TinyML with quantization and distillation of transformer and mamba models for indoor localisation on edge devices by Thanaphon Suwannaphong, Ferdian Jovan, Ian Craddock, Ryan McConville

“…The application of these TinyML models in healthcare has the potential to revolutionize patient monitoring by providing accurate, real-time location data while minimising power consumption, increasing data privacy, improving latency and reducing infrastructure costs.…”
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Enhancing IoT Security in Vehicles: A Comprehensive Review of AI-Driven Solutions for Cyber-Threat Detection by Rafael Abreu, Emanuel Simão, Carlos Serôdio, Frederico Branco, António Valente

“…Despite all the advances, challenges still remain in terms of data privacy and the scalability of AI solutions in IoT security. …”
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Applications of UAV Technologies in Assessment of Transportation Infrastructure Systems by Ahmad Akib Uz Zaman, Ahmed Abdelaty, Mohamed S. Yamany

“…Respondents emphasize the need for longer flight times, better automation, and advanced data tools, underscoring growing adoption and highlighting the need to overcome technical, regulatory, and data privacy challenges for optimal UAV integration within transportation infrastructure systems management.…”
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Cybersecurity and Major Cyber Threats of Smart Meters: A Systematic Mapping Review by Jones Márcio Nambundo, Otávio de Souza Martins Gomes, Adler Diniz de Souza, Raphael Carlos Santos Machado

“…These gaps include design requirements, software and firmware updates, physical security, the use of big data to detect vulnerabilities, user data privacy, and inconsistencies in machine learning algorithms. …”
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Mitochondrial disease registries worldwide: A scoping review. by Ammanie Abdul-Fatah, Leila Esmaeilisaraji, Crisel Mae Juan, Martin Holcik

“…These include establishing registry objectives, respecting patients and their roles in the registry, adopting international data standards, data evaluations, and considerations to privacy legislation, among others. …”
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Bibliometric analysis of digital transformation on organization design by Božić Katarina

“…Using the Bibliometrix software package in the R programming language, bibliographic data analysis was performed in order to identify the most influential authors, key topics and future research directions. …”
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The Potential for Large Language Models to Transform Cardiovascular Medicine (Russian Translation) by Quer, G., Topol, E.J.

“…Potential risks, such as loss of data privacy or potential diagnostic errors, should be addressed before use in clinical practice. …”
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Impact on bias mitigation algorithms to variations in inferred sensitive attribute uncertainty by Yanchen Wang, Lisa Singh

“…One approach to improve trustworthiness and fairness in AI systems is to use bias mitigation algorithms. However, most bias mitigation algorithms require data sets that contain sensitive attribute values to assess the fairness of the algorithm. …”
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Pooled Rideshare in the U.S.: An Exploratory Study of User Preferences by Rakesh Gangadharaiah, Johnell Brooks, Lisa Boor, Kristin Kolodge, Haotian Su, Yunyi Jia

“…The study incorporated 77 actionable items developed from the results of the 2021 survey to assess whether addressing specific user-generated topics such as safety, reliability, convenience, and privacy can improve pooled rideshare use. A side-by-side comparison of the 2021 and 2025 data revealed shifts in transportation behavior, with personal rideshare usage increasing from 22% to 28%, public transportation from 21% to 27%, and pooled rideshare from 6% to 8%, while personal vehicle (79%) use remained dominant. …”
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Digital insurance acceptance among older adults in the context of AI by Poorna Chandran K. R., Deepa Ittimani Tholath

“…This exploratory study employed the insights of the Technology Acceptance Model (TAM), the Information System Continuance Model (ISCM), and the Customer Satisfaction (C-SAT) method. Data were collected by conducting interviews in September 2024 with 20 older adults using AI-powered insurance services. …”
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Multimodal and Temporal Graph Fusion Framework for Advanced Phishing Website Detection by S. Kavya, D. Sumathi

“…FGCL-Net ensures privacy-preserving learning across decentralized datasets through federated contrastive learning, achieving 93-95% accuracy while safeguarding data privacy. …”
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