On the edge of glory (…or catastrophe): regulation, transparency and party democracy in data-driven campaigning in Québec by Eric Montigny, Philippe Dubois, Thierry Giasson

“…They have all massively integrated data-driven campaigning practices. This article identifies factors that could explain the increasing pressure to regulate Québec’s political parties’ uses of large sets of digital voter information. …”
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PERSONAL DATA PROTECTION ISSUE REFLECTED IN THE CASE-LAW OF THE CONSTITUTIONAL COURT OF ROMANIA by Valentina BĂRBĂȚEANU

“…Over the past few years, data privacy became more and more an issue that stirred on European level lots of debates and determined the adoption of a new set of rules, imposed with the compulsory force of a European regulation. …”
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A Set of Tools and Data Management Framework for the IoT–Edge–Cloud Continuum by Janis Judvaitis, Eduards Blumbergs, Audris Arzovs, Andris Ivars Mackus, Rihards Balass, Leo Selavo

“…The approach of the IECC Data Management Framework (DMF) introduces a novel combination of multiple easy-to-configure plugin environments using data visualization features. …”
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SAFED: secure and adaptive framework for edge-based data aggregation in IoT applications by Zaineb Naaz, Gamini Joshi, Vidushi Sharma

“…Based on requirements, the control center decrypts the aggregated data using its private key. Employing the Paillier cryptosystem for encryption and RSA for authentication, SAFED is fault-tolerant, maintaining functionality even if some IoT nodes fail. …”
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Secure K-Means Clustering Scheme for Confidential Data Based on Paillier Cryptosystem by Zhengqi Zhang, Zixin Xiong, Jun Ye

“…The protocol uses the additive homomorphism property of the Paillier cryptosystem to perform K-means clustering on the encrypted data, which ensures the confidentiality of the data during the whole calculation process. …”
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Complexity analysis and practical resolution of the data classification problem with private characteristics by David Pantoja, Ismael Rodríguez, Fernando Rubio, Clara Segura

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BeyondLife: An Open-Source Digital Will Solution for Posthumous Data Management by Xinzhang Chen, Arash Shaghaghi, Jesse Laeuchli, Salil S. Kanhere

“…Managing posthumous data is becoming an increasingly complex challenge, with many existing technical solutions proving impractical in real-world applications. …”
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Wasserstein GAN for moving differential privacy protection by Enze Liu, Zhiguang Chu, Xing Zhang

“…Abstract Training machine learning models often requires large datasets, but using sensitive data for training poses risks of privacy leakage. …”
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Protecting contacts against privacy leaks in smartphones. by Youngrok Cha, Wooguil Pak

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Deep Learning-Based Real Time Human Detection System Using LiDAR Data for Smart Healthcare Monitoring by Kalashtari Niloofar, Huhs Niklas, Kraitl Jens, Hornberger Christoph, Simanski Olaf

“…By training a YOLOv5 deep learning model using transfer learning, a method for accurate human detection and tracking within rooms using data collected from a digital LiDAR sensor was used. …”
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Privacy-Preserving Federated Class-Incremental Learning by Jue Xiao, Xueming Tang, Songfeng Lu

“…For privacy protection, we use Bayesian differential privacy to provide more balanced privacy protection for different datasets. …”
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Marketing Implications of Information Society Privacy Concerns by Gheorghe ORZAN, Călin VEGHEŞ, Cătălin SILVESTRU, Mihai ORZAN, Ramona BERE

“…The Internet has facilitated access to intimate user knowledge for both official and private agents and most of modern marketing strategies are based on a wealth of personal user data used to target its specific needs and expectations, a process that has its obvious pros and cons, which have been heavily debated intensively in both academic and social venues. …”
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An Enhanced Communication Protocol for Location Privacy in WSN by Abdel-Shakour Abuzneid, Tarek Sobh, Miad Faezipour

“…WSN is used in many applications, such as object tracking and security monitoring. …”
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Teenagers’ Digital Security: Sociological Analysis by Sergey G. Ushkin, Ekaterina A. Koval, Marina D. Martynova

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Determinants of Childbirth Choice in Rural Senegal: Mixed-Methods Analysis Using Data from the Niakhar Demographic Surveillance System by Pape Latyr Faye

“…Materials and methods: The study used a mixed-methods approach. Data from women who gave birth in the Niakhar observatory area between 1983 and 2020 were used, and chi-square tests and qualitative analyses were performed. …”
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Privacy protection scheme for mobile social network by Seyyed Mohammad Safi, Ali Movaghar, Mohammad Ghorbani

“…One way to protect one’s privacy is using encryption. Therefore, in the present paper, an improved secure design was presented for mobile social network using ciphertext-policy attribute-based encryption (CP-ABE) and advanced encryption standard (AES) that will encrypt users data in an end-to-end manner. …”
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Privacy-preserving task matching scheme for crowdsourcing by SONG Fuyuan, DING Siyang, WANG Wei, JIANG Qin, FU Zhangjie

“…Due to the potential untrustworthiness of crowdsourcing platforms, which may lead to the leakage of users’ private information, users are required to encrypt their data prior to uploading. To fulfill task matching while preserving privacy, the crowdsourcing platform employs encrypted spatial keyword queries to perform task matching of workers’ interests and locations. …”
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FedDBO: A Novel Federated Learning Approach for Communication Cost and Data Heterogeneity Using Dung Beetle Optimizer by Dongyan Wang, Limin Chen, Xiaotong Lu, Yidi Wang, Yue Shen, Jingjing Xu

“…After aggregating the model parameters sent by clients, the server performs a second iterative training on the aggregated model using its own metadata, thereby reducing data heterogeneity and improving model performance. …”
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Privacy-preserving maximum value determination scheme by Min Hou, Min Hou, Yue Wu

“…This paper introduces a quantum-secure scheme for conducting privacy-preserving maximum value determination, allowing the parties to ascertain the highest value from their confidential inputs while keeping non-maximum data private. …”
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Comparative Analysis of RAG-Based Open-Source LLMs for Indonesian Banking Customer Service Optimization Using Simulated Data by Hendra Lijaya, Patricia Ho, Handri Santoso

“…These findings underscore the potential of locally operated open-source LLMs for banking applications, ensuring privacy and regulatory compliance. However, limitations include reliance on synthetic data, a narrow question set, and lack of user diversity. …”
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