Privacy risk adaptive access control model via evolutionary game by Hongfa DING, Changgen PENG, Youliang TIAN, Shuwen XIANG

“…Aiming at the problem that in the private sensitive date centralized and opening information systems,a fine-grained and self-adaptive access control model for privacy preserving is desperately needed,thus the balance between privacy preserving and data access utility should be achieved,a rational multi-player risk-adaptive based access control model for privacy preserving was proposed.Firstly,the privacy risk values of access request and requester were formulized by the private information quantity of the requested dataset,and by using Shannon information.Secondly,a risk-adaptive based access control evolutionary game model was constructed by using evolutionary game under the supposing of bounded rational players.Furthermore,dynamic strategies of participants were analyzed by using replicator dynamics equation,and the method of choosing evolutionary stable strategy was proposed.Simulation and comparison results show that,the proposed model is effective to dynamically and adaptively preserve privacy and more risk adaptive,and dynamic evolutionary access strategies of the bounded rational participants are more suitable for practical scenarios.…”
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Preserving privacy and video quality through remote physiological signal removal by Saksham Bhutani, Mohamed Elgendi, Carlo Menon

“…However, the continuous and surreptitious recording of individuals by these devices and the collecting of sensitive health data without users’ knowledge or consent raise serious privacy concerns. …”
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Verifiable secure aggregation scheme for privacy protection in federated learning networks by Wujun Yao, Tanping Zhou, Yiliang Han, Xiaolin Wang

“…Security analysis demonstrates that our solution effectively ensures privacy protection. We tested the performance using a Raspberry Pi as an edge computing device. …”
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Impact of perceived privacy and security in the TAM model: The perceived trust as the mediated factors by Yan Zhang

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Analysis, Design, and Implementation of a User-Friendly Differential Privacy Application by Reynardo Tjhin, Muhammad Sajjad Akbar, Clement Canonne, Rabia Bashir

“…In the era of artificial intelligence, ensuring privacy in publicly released data is critical to prevent linkage attacks that can reveal sensitive information about individuals. …”
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Ethical and secure evidence generation from regionwide clinical data through a collaborative environment for advancing predictive care by Dolores Muñoyerro-Muñiz, Román Villegas, Víctor de la Oliva, Alberto Esteban-Medina, Patricia Fernández del Valle, Ana Sánchez, M. Belen Susin, Isidoro Gutierrez-Alvarez, Marta Reboredo, Laura Alejos, Carlos Loucera, Carlos Loucera, Joaquín Dopazo, Joaquín Dopazo

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Mobile Phone Network Data in the COVID-19 era: A systematic review of applications, socioeconomic factors affecting compliance to non-pharmaceutical interventions, privacy implicat... by Mohammed Okmi, Tan Fong Ang, Muhammad Faiz Mohd Zaki, Chin Soon Ku, Koo Yuen Phan, Irfan Wahyudi, Lip Yee Por

“…<h4>Background</h4>The use of traditional mobility datasets, such as travel surveys and census data, has significantly impacted various disciplines, including transportation, urban sensing, criminology, and healthcare. …”
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Can open source large language models be used for tumor documentation in Germany?—An evaluation on urological doctors’ notes by Stefan Lenz, Arsenij Ustjanzew, Marco Jeray, Meike Ressing, Torsten Panholzer

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Federated learning with LSTM for intrusion detection in IoT-based wireless sensor networks: a multi-dataset analysis by Raja Waseem Anwar, Mohammad Abrar, Abdu Salam, Faizan Ullah

“…Using an FL approach, multiple IoT nodes collaboratively train a global LSTM model without exchanging raw data, thereby addressing privacy concerns and improving detection capabilities. …”
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Federated learning in food research by Zuzanna Fendor, Bas H.M. van der Velden, Xinxin Wang, Andrea Jr. Carnoli, Osman Mutlu, Ali Hürriyetoğlu

“…The use of machine learning in food research is sometimes limited due to data sharing obstacles such as data ownership and privacy requirements. …”
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Federated meta learning: a review by Chuanyao ZHANG, Shijing SI, Jianzong WANG, Jing XIAO

“…With the popularity of mobile devices, massive amounts of data are constantly produced.The data privacy policies are becoming more and more specified, the flow and use of data are strictly regulated.Federated learning can break data barriers and use client data for modeling.Because users have different habits, there are significant differences between different client data.How to solve the statistical challenge caused by the data imbalance becomes an important topic in federated learning research.Using the fast learning ability of meta learning, it becomes an important way to train different personalized models for different clients to solve the problem of data imbalance in federated learning.The definition and classification of federated learning, as well as the main problems of federated learning were introduced systematically based on the background of federated learning.The main problems included privacy protection, data heterogeneity and limited communication.The research work of federated metalearning in solving the heterogeneous data, the limited communication environment, and improving the robustness against malicious attacks were introduced systematically starting from the background of federated meta learning.Finally, the summary and prospect of federated meta learning were proposed.…”
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Improved SpaceTwist privacy protection method based on anchor optimization algorithm by Zhen-peng LIU, Xuan ZHAO, Ya-wei DONG, Bin ZHANG

“…With location-based services worldwide used,private location data appealed easily in query process which caused serious security problems.So the introduction of SpaceTwist incremental nearest neighbor query algorithm,proposes protection of privacy method combined with improved SpaceTwist location optimization algorithm.The anchor point authentication server added to distributed system structure,user generate a k anonymous area according to their privacy preference and actual environment,using optimization algorithm to generate the anchor point.Forwarding users use the incremental nearest neighbor query throught the anchor point and accurate.Experiments in road network environment with different data sets show that the privacy protection works well in the algorithm,and own high work efficiency.…”
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Verticox+: vertically distributed Cox proportional hazards model with improved privacy guarantees by Florian van Daalen, Djura Smits, Lianne Ippel, Andre Dekker, Inigo Bermejo

“…Abstract Federated learning allows us to run machine learning algorithms on decentralized data when data sharing is not permitted due to privacy concerns. …”
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ETHICAL DIMENSIONS OF HUMAN RESOURCES AUDITING IN THE DIGITAL ERA by Alice STEFANESCU, Daria MARIN

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THE USE OF SOCIAL MEDIA FOR LEARNING ENGLISH: STUDENTS PERSPECTIVE by Muetia Safitri, Atik Yuliyani, Farida Hamid, Aminah Suriaman

“…Basic statistical analysis was used to analyze data from the questionnaire, and the data from interviews were analyzed using the flow model by Miles and Huberman. …”
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Chatbots in medicine: certification process and applied use case by Mayssam Nehme, Franck Schneider, Esther Amruthalingam, Elio Schnarrenberger, Raphaël Trëmeaud, Idris Guessous

“…However, their application in medicine and healthcare has been limited due to concerns over data privacy, ther risk of providing medical diagnoses, and ensuring regulatory and legal compliance. …”
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Artificial intelligence in neuroimaging: Opportunities and ethical challenges by Neha Brahma, S. Vimal

“…Issues such as algorithmic bias, data privacy, and the interpretability of AI-driven insights must be addressed to ensure that these technologies are used responsibly and equitably. …”
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Patient Perspective on Use of an Interactive Website for Sleep Apnea by Carl Stepnowsky, Christine Edwards, Tania Zamora, Robert Barker, Zia Agha

“…The goal of this paper is to report on CPAP adherence, internet use, privacy concerns and user satisfaction in using the website. …”
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Prioritizing privacy and presentation of supportable hypothesis testing in forensic genetic genealogy investigations by Bruce Budowle, Lee Baker, Antti Sajantila, Kristen Mittelman, David Mittelman

“…However, FGG generated genetic data contain private and sensitive information. Therefore, it is essential to deploy approaches that minimize unnecessary disclosure of these data to mitigate potential risks to individual privacy. …”
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Learning-augmented sketching offers improved performance for privacy preserving and secure GWAS by Junyan Xu, Kaiyuan Zhu, Jieling Cai, Can Kockan, Natnatee Dokmai, Hyunghoon Cho, David P. Woodruff, S. Cenk Sahinalp

“…To address this, methods like SkSES use sketching for genome-wide association studies (GWAS) across distributed datasets while maintaining privacy. …”
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