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Secure, privacy-preserving and federated machine learning in medical imaging
Nature Machine Intelligence, 2020 Georgios A Kaissis +2 more
exaly +2 more sources
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A survey on security and privacy of federated learning
Future generations computer systems, 2021Federated learning (FL) is a new breed of Artificial Intelligence (AI) that builds upon decentralized data and training that brings learning to the edge or directly on-device.
Viraaji Mothukuri +5 more
semanticscholar +1 more source
Disaster Privacy/Privacy Disaster
SSRN Electronic Journal, 2019AbstractPrivacy expectations during disasters differ significantly from nonemergency situations. This paper explores the actual privacy practices of popular disaster apps, highlighting location information flows. Our empirical study compares content analysis of privacy policies and government agency policies, structured by the contextual integrity ...
Madelyn R. Sanfilippo +4 more
openaire +1 more source
SSRN Electronic Journal, 2020
In a market where consumers choose between payment options and firms compete with products and prices, we show that payment data drives the formation of a market monopoly. A data-sharing policy can successfully restore and maintain a competitive market, but often at the expense of both efficiency and consumer welfare.
Garratt, Rod, Lee, Michael Junho
openaire +2 more sources
In a market where consumers choose between payment options and firms compete with products and prices, we show that payment data drives the formation of a market monopoly. A data-sharing policy can successfully restore and maintain a competitive market, but often at the expense of both efficiency and consumer welfare.
Garratt, Rod, Lee, Michael Junho
openaire +2 more sources
End-to-end privacy preserving deep learning on multi-institutional medical imaging
Nature Machine Intelligence, 2021 Using large, multi-national datasets for high-performance medical imaging AI systems requires innovation in privacy-preserving machine learning so models can train on sensitive data without requiring data transfer.
Georgios A Kaissis +2 more
exaly +2 more sources
2011
There was a time in the not-so-distant past when most people shared their life experiences via email or direct instant messaging (IM). With respect to privacy and security, it was a simpler time—users logged in directly to their email or IM accounts and sent links, pictures, and so on directly from their desktop or laptop to one or more specific ...
Chris Dannen, Christopher White
openaire +1 more source
There was a time in the not-so-distant past when most people shared their life experiences via email or direct instant messaging (IM). With respect to privacy and security, it was a simpler time—users logged in directly to their email or IM accounts and sent links, pictures, and so on directly from their desktop or laptop to one or more specific ...
Chris Dannen, Christopher White
openaire +1 more source
A Survey on Differential Privacy for Unstructured Data Content
ACM Computing Surveys, 2022Huge amounts of unstructured data including image, video, audio, and text are ubiquitously generated and shared, and it is a challenge to protect sensitive personal information in them, such as human faces, voiceprints, and authorships.
Ying Zhao, Jinjun Chen
semanticscholar +1 more source