Privacy-preserved data hiding using compressive sensing and fuzzy C-means clustering by Ming Li, Lanlan Wang, Haiju Fan

“…In this article, a novel scheme for data hiding in encrypted domain is proposed using fuzzy C-means clustering and compressive sensing technologies to protect privacy of the host image. …”
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Enhance differential privacy mechanisms for clinical data analysis using CNNs and reinforcement learning by Rakesh Batchala, Priyank Jain, Manasi Gyanchandani, Sanyam Shukla, Rajesh Wadhvani

“…The primary emphasis is on predicting and optimizing ventilation and sedation strategies for patients in Intensive Care Units. We safeguard patient data in the MIMIC-III dataset while preserving analytical utility by integrating differential privacy techniques, such as Gaussian, Laplace, Exponential, Zero-Concentrated, and Rényi mechanisms. …”
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Privacy-Preserving Healthcare Data Interactions: A Multi-Agent Approach Using LLMs by Carmen De Maio, Giuseppe Fenza, Domenico Furno, Teodoro Grauso, Vincenzo Loia

“…This study builds on prior research [1] by introducing a multi-agent system that uses Large Language Models (LLMs) for secure interactions with healthcare data. …”
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Comprehensive Review of Privacy, Utility, and Fairness Offered by Synthetic Data by A. Kiran, P. Rubini, S. Saravana Kumar

“…First and foremost, how well synthetic data can preserve privacy and control disclosure, second is how good is its utility, and third, are they able to give fair results without any bias when used in machine learning. …”
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Protecting Location Privacy for Outsourced Spatial Data in Cloud Storage by Feng Tian, Xiaolin Gui, Jian An, Pan Yang, Jianqiang Zhao, Xuejun Zhang

“…As a kind of spatial transformation method, Hilbert curve is widely used to protect the location privacy for spatial data. …”
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Explaining the unexplainable: data sharing and privacy in Web 3.0 by Shim Jieun, Kim Jieun

“…This study leverages explainable AI (XAI) to analyze user privacy behaviors and other privacy attributes, using data from 682 individuals in Korea within a personalized app scenario. …”
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Fair payments for privacy-preserving aggregation of mobile crowdsensing data by Mallikarjun Reddy Dorsala, V.N. Sastry, Sudhakar Chapram

“…To ensure the privacy of the data, privacy-preserving aggregation (PPA) has attracted much attention since it can find aggregated statistics on the encrypted data. …”
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Hilbert-Curve Based Data Aggregation Scheme to Enforce Data Privacy and Data Integrity for Wireless Sensor Networks by Yong-Ki Kim, Hyunjo Lee, Min Yoon, Jae-Woo Chang

“…To minimize communication cost, we utilize a tree-based network structure for constructing networks and aggregating data. To preserve data privacy, we make use of both a seed exchange algorithm and Hilbert-curve based data encryption. …”
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A Survey on Association Rule Hiding in Privacy Preserving Data Mining by Arezoo Hekmatyar, Naser Nematbakhsh, Mohammad Naderi Dehkordi

“…Data mining has been used as a public utility in extracting knowledge from databases during recent years. …”
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Wormhole Whispers: Reflecting User Privacy Data Boundaries Through Algorithm Visualization by Xiaoxiao Wang, Jingjing Zhang, Huize Wan, Yuan Yao

“…The primary contribution of this work is an innovative approach that uses metaphorical visual language to represent the flow of user data, algorithms, and information. …”
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Meta-analysis of privacy legal framework: revising the various approaches for balancing privacy risks and usability of healthcare information systems | Meta-analisi del quadro norm... by Matjaž Drev, Dalibor Stanimirović, Boštjan Delak

“…A proactive approach to managing these risks involves the use of privacy by design frameworks and conceptual tools. …”
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Exploring the association between cultural values and the intention to use digital data wallets by Varvara Keba, Tiago Oliveira, Melanie Trabandt

“…We developed a model to examine the intention to use digital data wallets – new privacy-enhancing tools based on the privacy calculus theory and Hofstede's cultural values. …”
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Study on choosing the parameter ε in differential privacy by Xian-mang HE, Sean WANGX, Hua-hui CHEN, Yi-hong DONG

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Security and privacy within smart cities by Putnik Nenad R., Marković Jana M.

“…However, the use of new technologies has raised many questions and caused concerns about the way these technologies are used and the possibilities of misuse of collected data. …”
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Privacy-Preserving Synthetic Data Generation Method for IoT-Sensor Network IDS Using CTGAN by Saleh Alabdulwahab, Young-Tak Kim, Yunsik Son

“…This study proposes a privacy-preserving synthetic data generation method using a conditional tabular generative adversarial network (CTGAN) aimed at maintaining the utility of IoT sensor network data for IDS while safeguarding privacy. …”
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Disease prevention versus data privacy: using landcover maps to inform spatial epidemic models. by Michael J Tildesley, Sadie J Ryan

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Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations by Marzieh Faridi Masouleh, Ali Harounabadi, Asal Sayyad

“…Studies show that the lack of a complete, efficient and standard model has caused many security flaws in these networks. By using the Internet limitations, this study discusses how to create a target function to protect data privacy in the Internet of Things. …”
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Enhancing privacy in IoT-based healthcare using provable partitioned secure blockchain principle and encryption by C. S. Madhumathi, K. Vishnu Kumar

“…Data sharing is a significant concern in healthcare because of privacy leakage and security issues. …”
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On the fidelity versus privacy and utility trade-off of synthetic patient data by Tim Adams, Colin Birkenbihl, Karen Otte, Hwei Geok Ng, Jonas Adrian Rieling, Anatol-Fiete Näher, Ulrich Sax, Fabian Prasser, Holger Fröhlich

“…Summary: The use of synthetic data is a widely discussed and promising solution for privacy-preserving medical research. …”
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Towards Self-Awareness Privacy Protection for Internet of Things Data Collection by Kok-Seng Wong, Myung Ho Kim

“…IoT-related applications are aiming to bring technology to people anytime and anywhere, with any device. However, the use of IoT raises a privacy concern because data will be collected automatically from the network devices and objects which are embedded with IoT technologies. …”
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