Blockchain-Enhanced Privacy and Security in Electronic Health Records: A Scalable Framework for Decentralised Data Management by Nagaraj Segar, Vijayarajan Vijayan

“…The framework uniquely integrates a sidechain-enabled blockchain architecture with hybrid encryption (AES-256/RSA and ECC), optimising both scalability and data protection, and is validated using the real-world MIMIC-III dataset. …”
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A Tailored Compliance Solution for Securing Personal Data privacy under Law 18-07 in Algeria by Mohamed kamel Benkaddour, Redouane Guettal, Ph.D

“…This article proposes the design and implementation of a computer application dedicated to compliance with Law 18-07 for the protection of personal data. We first collected and analyzed the legal requirements for data protection and then modeled them using UML diagrams following the UP methodology. …”
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Privacy in consumer wearable technologies: a living systematic analysis of data policies across leading manufacturers by Cailbhe Doherty, Maximus Baldwin, Rory Lambe, Marco Altini, Brian Caulfield

“…In this study, we systematically evaluated the privacy policies of 17 leading wearable technology manufacturers using a novel rubric comprising 24 criteria across seven dimensions: transparency, data collection purposes, data minimization, user control and rights, third-party data sharing, data security, and breach notification. …”
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Federated learning with differential privacy for breast cancer diagnosis enabling secure data sharing and model integrity by Shubhi Shukla, Suraksha Rajkumar, Aditi Sinha, Mohamed Esha, Konguvel Elango, Vidhya Sampath

“…This mitigates adversarial attacks and prevents data leakage. The proposed work uses the Breast Cancer Wisconsin Diagnostic dataset to address critical challenges such as data heterogeneity, privacy-accuracy trade-offs, and computational overhead. …”
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PPT-LBS: Privacy-preserving top-k query scheme for outsourced data of location-based services by Yousheng Zhou, Xia Li, Ming Wang, Yuanni Liu

“…However, while cloud server provides convenience and stability, it also leads to data security and user privacy leakage. Aiming at the problems of insufficient privacy protection and inefficient query in the existing LBS data outsourcing schemes, this paper presents a novel privacy-preserving top-k query for outsourcing situations. …”
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Efficient Privacy-Preserving Range Query With Leakage Suppressed for Encrypted Data in Cloud-Based Internet of Things by Sultan Basudan, Abdulrahman Alamer

“…To protect user privacy, the acquired data may be encrypted; however, this often presents challenges for efficiently searching the data. …”
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Privacy-based medical data protection against internal security threats in heterogeneous Internet of Medical Things by Muhammad Asif Habib, C M Nadeem Faisal, Shahzad Sarwar, Muhammad Ahsan Latif, Farhan Aadil, Mudassar Ahmad, Rehan Ashraf, Muazzam Maqsood

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Privacy-Preserving Poisoning-Resistant Blockchain-Based Federated Learning for Data Sharing in the Internet of Medical Things by Xudong Zhu, Hui Li

“…Although current blockchain-based federated learning (BFL) approaches aim to resolve these issues, two persistent security weaknesses remain: privacy leakage and poisoning attacks. This study proposes a privacy-preserving poisoning-resistant blockchain-based federated learning (PPBFL) scheme for secure IoMT data sharing. …”
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Spatio-Temporal Joint Planning for Integrated Energy Systems with Internet Data Center Considering Privacy Preservation by WU Chengbang, CHENG Zhijiang, LU Haifeng, YANG Handi

“…However， because both IDC and integrated energy systems （IES） possess underlying user information， data leakage may lead to various risks. Therefore， when designing collaborative optimization solutions for IDCs and IES， it is essential to consider the privacy preservation of both systems. …”
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Optimizing data privacy and security measures for critical infrastructures via IoT based ADP2S technique by Zhenyu Xu, Jinming Wang, Shujuan Feng, Salwa Othmen, Chahira Lhioui, Aymen Flah, Zdenek Slanina

“…This paper uses a reptile search optimization algorithm to offer attuned data protection with privacy scheme (ADP2S). …”
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Privacy-preserving multi-party data joint analysis scheme based on multiset operations in smart contracts by Xin Liu, Huize Gao, Dan Luo, Lanying Liang, Lu Peng, Yuchen Zhang, Shijie Jia, Gang Xu, Xiubo Chen, Baohua Zhang, Yu Gu

“…However, the demand for multi-party data joint analysis within these contracts faces challenges of privacy leakage and malicious deception. …”
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Enhanced Consumer Healthcare Data Protection Through AI-Driven TinyML and Privacy-Preserving Techniques by S. Aanjankumar, Monoj Kumar Muchahari, Shabana Urooj, Ishmeet Kaur, Rajesh Kumar Dhanaraj, Hanan Abdullah Mengash, S. Poonkuntran, Parag Ravikant Kaveri

“…The proposed method with TinyML looks at patient data, like ECG readings and reports of unusual heartbeats, right on local edge devices that have limited resources, enabled immediate privacy checks while using minimal computing power. …”
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Aerial pathways to resilience: the acceptance of drones in logistics transformation by Sofia Gomes, João M. Lopes, Tiago Trancoso

“…This study examines the determinants of consumer acceptance of drone delivery services, focusing on the roles of perceived usefulness, ease of use, and privacy concerns. We collected data from 1,108 Portuguese consumers through an online survey to assess how these factors influence consumer attitudes and intentions toward adopting drone delivery services. …”
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A Symmetric Projection Space and Adversarial Training Framework for Privacy-Preserving Machine Learning with Improved Computational Efficiency by Qianqian Li, Shutian Zhou, Xiangrong Zeng, Jiaqi Shi, Qianye Lin, Chenjia Huang, Yuchen Yue, Yuyao Jiang, Chunli Lv

“…By designing a new projection loss function and combining autoencoders with adversarial training, the proposed method effectively balances privacy protection and model utility. Experimental results show that, for financial time-series data tasks, the model using the projection loss achieves a precision of 0.95, recall of 0.91, and accuracy of 0.93, significantly outperforming the traditional cross-entropy loss. …”
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Using Homomorphic Proxy Re-Encryption to Enhance Security and Privacy of Federated Learning-Based Intelligent Connected Vehicles by Yang Bai, Yutang Rao, Hongyan Wu, Juan Wang, Wentao Yang, Gaojie Xing, Jiawei Yang, Xiaoshu Yuan

“…These threats can lead to the leakage of sensitive private data, such as location information and driving conditions. …”
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A Proposed Vision for Using Artificial Intelligence in Enhancing Strategic Value of Human Resources by Nadera Hourani

“…Yet, there are significant challenges in the form of algorithmic bias, data privacy concerns, and organizational readiness. …”
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Balancing Privacy and Performance: A Differential Privacy Approach in Federated Learning by Huda Kadhim Tayyeh, Ahmed Sabah Ahmed AL-Jumaili

“…Federated learning (FL), a decentralized approach to machine learning, facilitates model training across multiple devices, ensuring data privacy. However, achieving a delicate privacy preservation–model convergence balance remains a major problem. …”
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On the research for big data uses for public good purposes by Adeline Decuyper

“…Finally, aside from the opportunities, the mass production and use of data has also brought many challenges, such as evaluating the representativity of the data or handling threats to the privacy of users, that we will discuss in the last section of this article.…”
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Evaluating the effectiveness of data governance frameworks in ensuring security and privacy of healthcare data: A quantitative analysis of ISO standards, GDPR, and HIPAA in blockch... by Ameer Ahmed, Asjad Shahzad, Afshan Naseem, Shujaat Ali, Imran Ahmad

“…Although there are existing frameworks to govern healthcare data but they have certain limitations in effectiveness of data governance to ensure security and privacy. …”
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My Holistic Data Share: A WEB3 Data Share Application: Extending Beyond Finance to Privacy-Protected Decentralized Share of Multi-Dimensional Data to Enhance Global Healthcare by SATHYA KRISHNASAMY

“…This paper introduces a concept beyond cryptocurrencies and finance into everyday real-world use cases that need combinatorial access to a person’s holistic data, including financial and health records, genomic data, and advanced directives, among others, that need to be privacy protected and shared with specific actors identified for their roles in the WEB3 ecosystem through decentralized identifiers and non-fungible token badges identifying particular recipients. …”
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