Results 281 to 290 of about 64,505 (309)
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2018
In this chapter, we illustrate main results on privacy-preserving embeddings. Here, security properties of embeddings are analyzed by considering two possible scenarios for their use. In the first case, a client submits a query containing sensitive information to a server, which should respond to the query without gaining access to the private ...
Matteo Testa +3 more
openaire +1 more source
In this chapter, we illustrate main results on privacy-preserving embeddings. Here, security properties of embeddings are analyzed by considering two possible scenarios for their use. In the first case, a client submits a query containing sensitive information to a server, which should respond to the query without gaining access to the private ...
Matteo Testa +3 more
openaire +1 more source
Sociotechnical safeguards for genomic data privacy
Nature Reviews Genetics, 2022Zhiyu Wan +2 more
exaly
A Comprehensive Survey of Privacy-preserving Federated Learning
ACM Computing Surveys, 2022Xuefei Yin, Yanming Zhu, Jiankun Hu
exaly
Functional genomics data: privacy risk assessment and technological mitigation
Nature Reviews Genetics, 2021Gamze Gürsoy, Tianxiao Li, Susanna Liu
exaly
1998
One of the exciting mathematical developments of the past decade was the discovery of so-called uncrackable public key codes. These are codes with the characteristic that everyone knows the method of encryption, but the amount of calculation required for an outsider to break the code is considered beyond present computational capabilities.
openaire +1 more source
One of the exciting mathematical developments of the past decade was the discovery of so-called uncrackable public key codes. These are codes with the characteristic that everyone knows the method of encryption, but the amount of calculation required for an outsider to break the code is considered beyond present computational capabilities.
openaire +1 more source
Regulatory, safety, and privacy concerns of home monitoring technologies during COVID-19
Nature Medicine, 2020Sara Gerke, Carmel Shachar
exaly
A digital mask to safeguard patient privacy
Nature Medicine, 2022Lanqin Zhao, Youjin Hu, Jingchang Chen
exaly
When Machine Learning Meets Privacy in 6G: A Survey
IEEE Communications Surveys and Tutorials, 2020Yuanyuan Sun, Jiajia Liu, Jiadai Wang
exaly