When Forcing Collaboration is the Most Sensible Choice: Desirability of Precautionary and Dissuasive Mechanisms to Manage Multiparty Privacy Conflicts

Autor: Henri Keopraseuth, Kavous Salehzadeh Niksirat, Marc-Olivier Boldi, Mauro Cherubini, Kévin Huguenin, Jose M. Such

Publikováno v: Proceedings of the ACM on Human-Computer Interaction
Proceedings of the ACM on Human-Computer Interaction, Association for Computing Machinery (ACM), 2021, 5 (CSCW1), pp.53:1-53:36. ⟨10.1145/3449127⟩
Proceedings of the ACM on Human-Computer Interaction (PACMHCI) / ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), vol. 5, no. CSCW1, pp. 53:1-53:36

Presented at the ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW); International audience; Individuals share increasing amounts of personal multimedia data, exposing themselves (uploaders) as well as others (data subj

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Secure Logistic Regression for Vertical Federated Learning

Autor: Daojing He, Runmeng Du, Shanshan Zhu, Min Zhang, Kaitai Liang, Sammy Chan

Publikováno v: IEEE Internet Computing, 26(2)

Data island effectively blocks the practical application of machine learning. To meet this challenge, a new framework known as federated learning was created. It allows model training on a large amount of scattered data owned by different data provid

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http://resolver.tudelft.nl/uuid:a0b91646-09f2-4e54-a47b-378cb71b2292

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