Privacy-Conducive Data Ecosystem Architecture: By-Design Vulnerability Assessment Using Privacy Risk Expansion Factor and Privacy Exposure Index by Ionela Chereja, Rudolf Erdei, Daniela Delinschi, Emil Pasca, Anca Avram, Oliviu Matei

“…The increasing complexity of data ecosystems demands advanced methodologies for systematic privacy risk assessment. …”
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Solving Truthfulness-Privacy Trade-Off in Mixed Data Outsourcing by Using Data Balancing and Attribute Correlation-Aware Differential Privacy by Abdul Majeed, Seong Oun Hwang

“…Anonymization methods are mostly used in data outsourcing to protect privacy; however, it is very hard to apply anonymity to datasets of poor quality while maintaining an equilibrium between privacy, utility, and truthfulness (i.e., ensuring the values in anonymized data are consistent with the real data). …”
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Crowdsourced data leaking user's privacy while using anonymization technique by Naadiya Mirbahar Mirbahar, Kamlesh Kumar, Asif Ali Laghari, Mansoor Ahmed Khuhro

“…However, this may pose privacy risks to data owners, even though the data collectors usually anonymize the data before crowdsourcing. …”
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Addressing contemporary threats in anonymised healthcare data using privacy engineering by Sanjiv M. Narayan, Nitin Kohli, Megan M. Martin

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Sharing Privacy Protected and Statistically Sound Clinical Research Data Using Outsourced Data Storage by Geontae Noh, Ji Young Chun, Ik Rae Jeong

“…Researchers are able to obtain valuable information that they would not otherwise be able to access; however, privacy concerns arise when sharing clinical data in these outsourced publicly available data storage services. …”
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INSURANCE DEVELOPMENTS IN THE LIGHT OF DATA USE by NADJIA, Madaoui

“…It aims to assess the extent to which existing legal regulations can safeguard policyholders from potential mistreatment resulting from the use of such methodologies. The study concludes that despite the safeguards offered by data and consumer protection laws, the unregulated and unconstrained application of data analytics and algorithms in risk evaluation could potentially harm policyholders by infringing on their privacy and leading to discrimination, thereby impinging on their rights.…”
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Towards Privacy-Aware and Trustworthy Data Sharing Using Blockchain for Edge Intelligence by Youyang Qu, Lichuan Ma, Wenjie Ye, Xuemeng Zhai, Shui Yu, Yunfeng Li, David Smith

“…Linkage attack is a type of dominant attack in the privacy domain, which can leverage various data sources for private data mining. …”
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Design of Privacy Preservation Model for Data Stream Using Condensation Based Anonymization by Latha P, Thangaraj M

“…The condensation method minimizes lost information throughout the anonymization process in an effort to maintain the statistical features of the data. Using generalization and suppression approaches, k-Anonymity obscures identifying information in datasets, making it a useful tool for protecting individual privacy. …”
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Privacy-preserving recommender system using the data collaboration analysis for distributed datasets. by Tomoya Yanagi, Shunnosuke Ikeda, Noriyoshi Sukegawa, Yuichi Takano

“…To this end, we establish a framework for privacy-preserving recommender systems using the data collaboration analysis of distributed datasets. …”
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Survey of split learning data privacy by QIN Yiqun, MA Xiaojing, FU Jiayun, HU Pingyi, XU Peng, JIN Hai

“…In response to these concerns, the Personal Information Protection Law of the People's Republic of China was promulgated to regulate the collection, use, and transmission of private information. Despite this, machine learning requires a large amount of data, necessitating the development of privacy protection technologies that allow for the collection and processing of data under legal and compliant conditions. …”
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Can Synthetic Data Protect Privacy? by Gidan Min, Junhyoung Oh

“…To systematically evaluate the privacy protection performance of synthetic data generation algorithms (Synthpop, CTGAN, RTVAE, TVAE, DataSynthesizer), this study applied various safety metrics. …”
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Towards a privacy debt by Xabier Larrucea, Izaskun Santamaría, Manuel Graña Romay

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Adaptive personalized privacy-preserving data collection scheme with local differential privacy by Haina Song, Hua Shen, Nan Zhao, Zhangqing He, Wei Xiong, Minghu Wu, Mingwu Zhang

“…Local differential privacy (LDP) is a state-of-the-art privacy notion that enables terminal participants to share their private data safely while controlling the privacy disclosure at the source. …”
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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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Protecting Privacy on Social Media: Mitigating Cyberbullying and Data Heist Through Regulated Use and Detox, with a Mediating Role of Privacy Safety Motivations by Jing Niu, Bilal Mazhar, Inam Ul Haq, Fatima Maqsood

“…Information theft and cyberbullying pose significant threats to users’ privacy on social media. This study applies Protection Motivation Theory (PMT) to explore how online information disclosure awareness and privacy concerns influence protective actions, such as regulated social media usage and detoxification, in response to negative experiences like data heist and cyberbullying. …”
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An accuracy-privacy optimization framework considering user’s privacy requirements for data stream mining by Waruni Hewage, R. Sinha, M. Asif Naeem

“…Additionally, a data fitting module using kernel regression is integrated, a unique approach that predicts accuracy levels based on user-defined privacy thresholds. …”
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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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Data Anonymization and Privacy Preservation in Healthcare Systems by Datta Krishnasheesh, Gupta Himanshu

“…With the objective to identify key trends and driving factors, a bibliometric analysis was performed using VOSviewer, which focuses on prominent authors, dominant research topics, and collaborative networks in data privacy. …”
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