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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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

“…As user interactions on online social platforms increase, so does the public’s concern over the exposure of user privacy data. However, ordinary users often lack a clear and intuitive understanding of how their personal online information flows and how algorithms are involved in this process. …”
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Ethical Dilemmas and Coping Strategies in the Use of Psychological Scales in the Era of Big Data by Lirong LIU, Yanan ZHENG

“…Focusing on the ethical risks arising from the reconstruction of psychological scales due to innovations in big data technology, a systematic analysis is conducted on the research and current use of psychological scales within the context of big data. …”
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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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A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystem by Shreyansh Sharma, Debasis Das, Santanu Chaudhury

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Federated LeViT-ResUNet for Scalable and Privacy-Preserving Agricultural Monitoring Using Drone and Internet of Things Data by Mohammad Aldossary, Jaber Almutairi, Ibrahim Alzamil

“…New drone photography and IoT sensors offer quick, high-resolution, multimodal agricultural data collecting. Regional diversity, data heterogeneity, and privacy problems make it hard to conclude these data. …”
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Enhancing Data Privacy Protection and Feature Extraction in Secure Computing Using a Hash Tree and Skip Attention Mechanism by Zizhe Zhou, Yaqi Wang, Lin Cong, Yujing Song, Tianyue Li, Meishu Li, Keyi Xu, Chunli Lv

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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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Privacy-Aware Detection for Large Language Models Using a Hybrid BiLSTM-HMM Approach by Maryam Abbasalizadeh, Sashank Narain

“…However, their deployment introduces significant privacy concerns, including the memorization and unintended disclosure of sensitive data. …”
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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 Rule Induction Using CKKS by Jihyeon Choi, Jina Choi, Younho Lee, Jung-Sik Hong

“…This study introduces a new approach called homomorphic encryption-based rule induction (HORI) algorithm, designed specifically for scenarios where data confidentiality is critical. This method is constructed using CKKS homomorphic encryption to make it work with encrypted data, thereby enhancing the privacy of both training data and the input for inference. …”
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Safer interaction with IVAs: The impact of privacy literacy training on competent use of intelligent voice assistants by André Markus, Maximilian Baumann, Jan Pfister, Astrid Carolus, Andreas Hotho, Carolin Wienrich

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Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data by Shiyue Qin, Fucai Zhou, Zongye Zhang, Zifeng Xu

“…Substring searching on gene sequence data is widely used for analyzing the association between a list of gene mutations and a specific disease. …”
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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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Data Fusion and Processing Technology of Wireless Sensor Network for Privacy Protection by Lusheng Shi, Kai Li, Huibo Zhu

“…Data fusion and privacy protection technologies are both the research focuses in the field of wireless sensor networks. …”
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Review of privacy computing techniques for multi-party data fusion analysis by LIU Shenglong, HUANG Xiuli, JIANG Yiwen, JIANG Jiawei, TIAN Yuechi, ZHOU Zejun, NIU Ben

“…In the data era, threats to personal privacy information in ubiquitous sharing environments are widespread, such as apps frequently collecting personal information beyond scope, and big data-enabled price discrimination against frequent customers. …”
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A hybrid-security model for privacy-enhanced distributed data mining by Tanzeela Javid, Manoj Kumar Gupta, Abhishek Gupta

“…The accuracy obtained in classification task and clustering task using naïve Bayes and k-means technique is high when different datasets in a privacy-enhanced distributed data mining environment verify the working of the hybrid security model.…”
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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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