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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Data Privacy Protection in Islamic Communication Perspective by Musfiah Saidah, Hilya Maylaffayza

“…Technology in the era of society 5.0 was rising to facilitate human work, but it is used to misuse big data from the individual level. …”
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Privacy-Preserving Data Sharing in Telehealth Services by Ammar Odeh, Eman Abdelfattah, Walid Salameh

“…Telehealth services, while providing immense benefits in terms of accessibility and efficiency, introduce complex challenges in maintaining data privacy and security. This paper proposes a privacy-preserving framework for secure data sharing within telehealth services, employing blockchain technology and advanced cryptographic techniques. …”
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Privacy-Preserving Synthetic Data Generation Method for IoT-Sensor Network IDS Using CTGAN by Saleh Alabdulwahab, Young-Tak Kim, Yunsik Son

“…This study proposes a privacy-preserving synthetic data generation method using a conditional tabular generative adversarial network (CTGAN) aimed at maintaining the utility of IoT sensor network data for IDS while safeguarding privacy. …”
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Disease prevention versus data privacy: using landcover maps to inform spatial epidemic models. by Michael J Tildesley, Sadie J Ryan

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Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations by Marzieh Faridi Masouleh, Ali Harounabadi, Asal Sayyad

“…Studies show that the lack of a complete, efficient and standard model has caused many security flaws in these networks. By using the Internet limitations, this study discusses how to create a target function to protect data privacy in the Internet of Things. …”
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Unpacking Youth Privacy Management in AI Systems: A Privacy Calculus Model Analysis by Austin Shouli, Ankur Barthwal, Molly Campbell, Ajay Kumar Shrestha

“…The increasing use of Artificial Intelligence (AI) in daily life has introduced substantial issues in protecting user privacy, particularly for young digital citizens. …”
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Blockchain-enabled data governance for privacy-preserved sharing of confidential data by Jingchi Zhang, Anwitaman Datta

“…Our novel ABE encryption system supports multi-authority use cases while hiding access policy and ensuring identity privacy, which also protects data sharing against corrupt authorities. …”
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Combining observational and experimental data for causal inference considering data privacy by Mann Charlotte Z., Sales Adam C., Gagnon-Bartsch Johann A.

“…However, many observational datasets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. …”
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Enhancing privacy in IoT-based healthcare using provable partitioned secure blockchain principle and encryption by C. S. Madhumathi, K. Vishnu Kumar

“…Data sharing is a significant concern in healthcare because of privacy leakage and security issues. …”
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Perturbation based privacy preservation and classification using Jaya Algorithm and Dragonfly Inspired Algorithm by Dipanwita Sen, Bhupati Bhusan Mishra, Prasant Kumar Pattnaik

“…That is why, privacy preservation of data for healthcare dataset is a significant consideration. …”
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Privacy in the Internet: Myth or reality by Mikarić Bratislav, Marković Marija, Trajković Dušan

“…The present time, unthinkable without using Internet - from e-mail, through social networks, cloud services, GPS, to YouTube and mobile computing in business, as well as on a private level, poses a question: Is there a way to protect data and their privacy on the Internet? …”
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Secure data sharing technology of medical privacy data in the Web 3.0 by Shusheng Guo, Cheng Chen, Qing Tong

“…Finally, data users apply to multiple parties for joint secure computing to obtain the use of private data. …”
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Privacy guarantees for personal mobility data in humanitarian response by Nitin Kohli, Emily Aiken, Joshua E. Blumenstock

“…Specifically, we (1) introduce an algorithm for constructing differentially private mobility matrices and derive privacy and accuracy bounds on this algorithm; (2) use real-world data from mobile phone operators in Afghanistan and Rwanda to show how this algorithm can enable the use of private mobility data in two high-stakes policy decisions: pandemic response and the distribution of humanitarian aid; and (3) discuss practical decisions that need to be made when implementing this approach, such as how to optimally balance privacy and accuracy. …”
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Privacy protection method on time-series data publication by Dong YU, Hai-yan KANG

“…A differential privacy model was proposed based on the sampling filtering and the mechanism of evaluation.Firstly,fixed sampling method was used to sample the original data and the non-sampling data be published directly.Secondly,for the sampling date,utilize the differential privacy mechanism to add the noise.Then,use Kalman to correct the sampling date.Finally,use the mutual information to evaluate data under different sampling intervals.Through the experiment,it is proved that the mechanism can achieve a good balance between the practicality and protective.…”
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Synthetic data for privacy-preserving clinical risk prediction by Zhaozhi Qian, Thomas Callender, Bogdan Cebere, Sam M. Janes, Neal Navani, Mihaela van der Schaar

“…Compared with other privacy-enhancing approaches—such as federated learning—analyses performed on synthetic data can be applied downstream without modification, such that synthetic data can act in place of real data for a wide range of use cases. …”
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Proactive Data Categorization for Privacy in DevPrivOps by Catarina Silva, João P. Barraca, Paulo Salvador

“…PsDC is a data-categorization model designed for integration with the DevPrivOps methodology and for use in privacy-quantification models. …”
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DPLQ: Location‐based service privacy protection scheme based on differential privacy by Qingyun Zhang, Xing Zhang, Mingyue Wang, Xiaohui Li

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Enhancing healthcare data privacy and interoperability with federated learning by Adil Akhmetov, Zohaib Latif, Benjamin Tyler, Adnan Yazici

“…Unlike traditional centralized learning (CL) solutions that require data centralization, our platform uses local model learning, which naturally improves data privacy. …”
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Aggregated privacy-preserving auditing for cloud data integrity by Kai HE, Chuan-he HUANG, Xiao-mao WANG, Jing WANG, Jiao-li SHI

“…To solve the problem of data integrity in cloud storage,an aggregated privacy-preserving auditing scheme was proposed.To preserve data privacy against the auditor,data proof and tag proof were encrypted and combined by using the bilinearity property of the bilinear pairing on the cloud server.Furthermore,an efficient index mechanism was designed to support dynamic auditing,which could ensure that data update operations did not lead to high additional computation or communication cost.Meanwhile,an aggregation method for different proofs was designed to handle multiple auditing requests.Thus the proposed scheme could also support batch auditing for multiple owners and multiple clouds and multiple files.The communication cost of batch auditing was independent of the number of auditing requests.The theoretical analysis and experimental results show that the proposed scheme is provably secure.Compared with existing auditing scheme,the efficacy of the proposed individual auditing and batch auditing improves 21.5% and 31.8% respectively.…”
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