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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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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Ethical Considerations in Emotion Recognition Research by Darlene Barker, Mukesh Kumar Reddy Tippireddy, Ali Farhan, Bilal Ahmed

“…The framework introduces structural safeguards which include data minimization, adaptive consent mechanisms, and transparent model logic as a more complete solution than privacy or fairness approaches. …”
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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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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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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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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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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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Teenagers’ Digital Security: Sociological Analysis by Sergey G. Ushkin, Ekaterina A. Koval, Marina D. Martynova

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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

“…As an emerging distributed machine learning technology, federated learning has gained widespread attention due to its critical privacy protection mechanism. However, it also faces challenges such as high communication costs and heterogeneous client data.In order to address the above issues. …”
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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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Record linkage without patient identifiers: Proof of concept using data from South Africa's national HIV program. by Khumbo Shumba, Jacob Bor, Cornelius Nattey, Dickman Gareta, Evelyn Lauren, William Macleod, Matthew P Fox, Adrian Puren, Koleka Mlisana, Dorina Onoya

“…Linkage variables were result value, specimen collection date, facility of collection, year and month of birth, and sex. We used three matching strategies: exact matching on exact values of all variables, caliper matching allowing a ± 5 day window on result date, and specimen barcode matching using unique specimen identifiers. …”
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Study on privacy preserving encrypted traffic detection by Xinyu ZHANG, Bingsheng ZHANG, Quanrun MENG, Kui REN

“…Existing encrypted traffic detection technologies lack privacy protection for data and models, which will violate the privacy preserving regulations and increase the security risk of privacy leakage.A privacy-preserving encrypted traffic detection system was proposed.It promoted the privacy of the encrypted traffic detection model by combining the gradient boosting decision tree (GBDT) algorithm with differential privacy.The privacy-protected encrypted traffic detection system was designed and implemented.The performance and the efficiency of proposed system using the CICIDS2017 dataset were evaluated, which contained the malicious traffic of the DDoS attack and the port scan.The results show that when the privacy budget value is set to 1, the system accuracy rates are 91.7% and 92.4% respectively.The training and the prediction of our model is efficient.The training time of proposed model is 5.16 s and 5.59 s, that is only 2-3 times of GBDT algorithm.The prediction time is close to the GBDT algorithm.…”
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