Enhancing privacy in clustering and data mining: A novel approach for sensitive data protection by Haythem Hayouni

“…However, these processes often involve the use of sensitive data, raising significant concerns about privacy, security, and trustworthiness. …”
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Right to privacy, Big Data and data protection: new challenges of the Colombian legal system by Dayron Dannylo Reyes Quintero, Margarita Rosa Lobo Contreras, Lucía Dayana Amaya Barbosa

“…Also, the perception and characteristics of Big Data are disclosed, trying to know how the rights involved in the materialization of the data analysis process can be protected; Finally, a critical sense is applied to the use of Big Data in modern political platforms, understanding the panorama for the Colombian legal system, which brings with it the probable violation of fundamental rights, such as personal privacy.…”
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Data structure and privacy protection analysis in big data environment based on blockchain technology by Yu Wang

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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

“…With the advent of mobile crowdsensing, the mobile devices equipped with a variety of sensors (such as accelerometer, gyroscope, microphone etc.) are used to collect sensory data. A data aggregator processes the collected sensor data to deliver various services such as traffic management, health care and environmental monitoring. …”
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Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Current studies focus mainly on correlations between data and pain levels, but rarely use this information for accurate prediction.ObjectiveThis study aims to review recent advancements in wearable technology for CP management, emphasizing the integration of multimodal data, sensor quality, compliance with data security standards, and the effectiveness of predictive models in identifying CP episodes.MethodsA systematic search across six major databases identified studies evaluating wearable devices designed to collect pain-related parameters and predict CP. …”
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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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Abnormality detection and privacy protection strategies for power marketing inspection business of cyber–physical–social systems using big data and artificial intelligence by Li Kai, Mo Pingyan, Yang Yongjiao, Xie Hanyang, Shen Zhixiong

“…Subsequently, the fault interval detection algorithm is used to locate fault periods, and the electricity consumed within these intervals is dynamically estimated using a prediction algorithm. …”
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Developing a Model for Protecting the Privacy of Internet Customers in the Field of Health by Zahra Sharifi, Mohammad Ali Keramati, Mehrzad Minooei

“…In this area, there is sensitive and personal information, and privacy can increase customers’ trust in companies and create a stronger relationship between them.Methods: The target sample was chosen using a criterion-oriented purposeful sampling method. …”
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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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Privacy-utility tradeoff method using multi-variable source coding by Yong-hao GU, Jiu-chuan LIN

“…In the age of big data,data providers need to ensure their privacy,while data analysts need to mine the value of data.So,how to find the privacy-utility tradeoff has become a research hotspot.Current works mostly focus on privacy preserving methods,ignoring the data utility.Based on the current research of privacy utility equilibrium methods,a privacy-utility tradeoff method using multi-variable source coding was proposed to solve the problem that different public datasets in the same database have different privacy requirements.Two results are obtained by simulations.The first result is that the greater the association degree between the private information and public information,the increase of the distortion degree of public information will significantly improve the effect of privacy preservation.The second result is that public information with larger variance should be less distorted to ensure more utility.…”
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Deepfake Image Forensics for Privacy Protection and Authenticity Using Deep Learning by Saud Sohail, Syed Muhammad Sajjad, Adeel Zafar, Zafar Iqbal, Zia Muhammad, Muhammad Kazim

“…This research focuses on the detection of deepfake images and videos for forensic analysis using deep learning techniques. It highlights the importance of preserving privacy and authenticity in digital media. …”
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Revisiting the use and effectiveness of patient-held records in rural Malawi by Amelia Taylor, Paul Kazembe

“…Aim This paper assessed their use and effectiveness within the health data ecosystem, and their potential impact on patient care. …”
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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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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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