ScholarIQanswers from OpenAlex
Privacy-Preserving Technologies in Data
TopicLeading institutions, researchers & key papers
Privacy-Preserving Technologies in Data is a topic indexed in ScholarIQ from OpenAlex.
What is known about Privacy-Preserving Technologies in Data?
ScholarIQrecord summary
This cluster of papers focuses on privacy-preserving techniques for data analysis and machine learning, including topics such as differential privacy, federated learning, k-anonymity, secure computation, and location privacy. The papers explore methods to protect sensitive information while performing data mining, machine learning, and statistical analysis.
How many works does Privacy-Preserving Technologies in Data have?
ScholarIQindexed works
Privacy-Preserving Technologies in Data has 90 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.
What is the OpenAlex record for Privacy-Preserving Technologies in Data?
ScholarIQopenalex
The OpenAlex for Privacy-Preserving Technologies in Data is on the source record.
What are the most-cited papers on Privacy-Preserving Technologies in Data?
ScholarIQmost cited works
A Clustering Approach for the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mi>l</mml:mi></mml:mrow></mml:math>-Diversity Model in Privacy Preserving Data Mining Using Fractional Calculus-Bacterial Foraging Optimization Algorithm
Pawan Bhaladhare, Devesh C. Jinwala
FedProc: Prototypical contrastive federated learning on non-IID data
Xutong Mu, Yulong Shen, Ke Cheng, Xueli Geng, Jiaxuan Fu, Tao Zhang, Zhiwei Zhang
Aspects of privacy for electronic health records
Sebastian Haas, Sven Wohlgemuth, Isao Echizen, Noboru Sonehara, Günter Müller
Review on security of federated learning and its application in healthcare
Hao Li, Chengcheng Li, Jian Wang, Aimin Yang, Zezhong Ma, Zunqian Zhang, Dianbo Hua
A Probabilistic Approach for Cooperative Computation Offloading in MEC-Assisted Vehicular Networks
Penglin Dai, Kai‐Wen Hu, Xiao Wu, Huanlai Xing, Fei Teng, Zhaofei Yu
Where is Privacy-Preserving Technologies in Data research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock
How much of the research on Privacy-Preserving Technologies in Data is open access?
ScholarIQopen access share
33%OPEN ACCESS