Protecting contacts against privacy leaks in smartphones. by Youngrok Cha, Wooguil Pak

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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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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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Clinical Simulation Program for the Training of Health Profession Residents in Confidentiality and the Use of Social Networks by Alejandro Martínez-Arce, Alberto Bermejo-Cantarero, Laura Muñoz de Morales-Romero, Víctor Baladrón-González, Natalia Bejarano-Ramírez, Gema Verdugo-Moreno, María Antonia Montero-Gaspar, Francisco Javier Redondo-Calvo

“…After the course, the participants reported intending to modify their behavior when sharing patient data without their consent and with respect to how patients are informed; Conclusions: The use of advanced simulation in the training of interprofessional teams of residents is as an effective tool for initiating attitudinal change and increasing knowledge related to patient privacy and confidentiality. …”
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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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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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Revolutionizing healthcare data analytics with federated learning: A comprehensive survey of applications, systems, and future directions by Nisha Thorakkattu Madathil, Fida K. Dankar, Marton Gergely, Abdelkader Nasreddine Belkacem, Saed Alrabaee

“…In general, through systematic categorization and analysis of existing FL systems, we offer insights to design efficient, accurate, and privacy-preserving healthcare applications using cutting-edge FL techniques.…”
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Community views on the secondary use of general practice data: Findings from a mixed‐methods study by Annette J. Braunack‐Mayer, Carolyn Adams, Alberto Nettel‐Aguirre, Belinda Fabrianesi, Lucy Carolan, Justin Beilby, Felicity Flack

“…Abstract Introduction General practice data, particularly when combined with hospital and other health service data through data linkage, are increasingly being used for quality assurance, evaluation, health service planning and research. …”
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Self-sovereign management scheme of personal health record with personal data store and decentralized identifier by Tong Min Kim, Taehoon Ko, Byoung Woo Hwang, Hyung Goo Paek, Wan Yeon Lee

“…Conventional personal health record (PHR) management systems are centralized, making them vulnerable to privacy breaches and single points of failure. Despite progress in standardizing healthcare data with the FHIR format, hospitals often lack efficient platforms for transferring PHRs, leading to redundant tests and delayed treatments. …”
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PERSONAL DATA PROTECTION IN CRIMINAL PROCEEDINGS by SMOLKOVA Iraida Vyacheslavovna

“…The most vulnerable to these factors are the privacy and personal data of participants in criminal proceedings. …”
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Federated Learning Model Using CBDPL for Medical Image Segmentation by K. Hemalatha, Shradhanjali Das

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Efficient Keyset Design for Neural Networks Using Homomorphic Encryption by Youyeon Joo, Seungjin Ha, Hyunyoung Oh, Yunheung Paek

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When Two are Better Than One: Synthesizing Heavily Unbalanced Data by Francisco Ferreira, Nuno Lourenco, Bruno Cabral, Joao Paulo Fernandes

“…However, they need to fully comply with not only ethical but also regulatory obligations, where, e.g., privacy (strictly) needs to be respected when using or sharing data, thus protecting both the interests of users and organizations. …”
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Neurorights, Neurotechnologies and Personal Data: Review of the Challenges of Mental Autonomy by Y. Cornejo

“…Thorough searches were carried out with the search terms “neurotechnology”, “personal data”, “mental privacy”, “neuro-rights”, “neurotechnological interventions”, and “neurotechnological discrimination” on both English and Spanish sites, using search engines like Google Scholar and Redib as well as databases including Scielo, Dialnet, Redalyc, Lilacs, Scopus, Medline, and Pubmed. …”
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Proposed ethical framework for software requirements engineering by Seblewongel E. Biable, Nuno M. Garcia, Dida Midekso

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Advanced Zero-Shot Learning (AZSL) Framework for Secure Model Generalization in Federated Learning by Muhammad Asif, Surayya Naz, Faheem Ali, Amerah Alabrah, Abdu Salam, Farhan Amin, Faizan Ullah

“…The objective of the proposed model is to increase model generalizability while achieving better performance on various and heterogeneous datasets while preserving data privacy. We have used datasets named MNIST, CIFAR-10, and FEMNIST to measure the model’s accuracy, precision, and generalization capability. …”
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Time Series Classification Using Federated Convolutional Neural Networks and Image-Based Representations by Felipe A. R. Silva, Omid Orang, Fabricio Javier Erazo-Costa, Petronio C. L. Silva, Pedro H. Barros, Ricardo P. M. Ferreira, Frederico Gadelha Guimaraes

“…Federated Learning (FL) enables collaborative training across distributed clients while ensuring data privacy. The method’s effectiveness is evaluated using 40 datasets from the UCR Archive. …”
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Federated target trial emulation using distributed observational data for treatment effect estimation by Haoyang Li, Chengxi Zang, Zhenxing Xu, Weishen Pan, Suraj Rajendran, Yong Chen, Fei Wang

“…Abstract Target trial emulation (TTE) aims to estimate treatment effects by simulating randomized controlled trials using real-world observational data. Applying TTE across distributed datasets shows great promise in improving generalizability and power but is always infeasible due to privacy and data-sharing constraints. …”
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