Fast Cryptographic Multi-Party Protocols for Computing Boolean Scalar Products with Applications to Privacy-Preserving Association: Rule Mining in Vertically Partitioned Data - researchr publication related

researchr

You are not signed in
Sign in
Sign up

Dragos Trinca, Sanguthevar Rajasekaran. Fast Cryptographic Multi-Party Protocols for Computing Boolean Scalar Products with Applications to Privacy-Preserving Association: Rule Mining in Vertically Partitioned Data. In Isabelle Bichindaritz, Petra Perner, editors, Advances in Data Mining. 7th Industrial Conference, ICDM 2007, Leipzig, Germany, July 2007, Poster and Workshop Proceedings. IBaI Report, pages 86, 2007.

The following publications are possibly variants of this publication:

Fast Cryptographic Multi-party Protocols for Computing Boolean Scalar Products with Applications to Privacy-Preserving Association Rule Mining in Vertically Partitioned DataDragos Trinca, Sanguthevar Rajasekaran. dawak 2007: 418-427 [doi]

Towards a Collusion-Resistant Algebraic Multi-Party Protocol for Privacy-Preserving Association Rule Mining in Vertically Partitioned DataDragos Trinca, Sanguthevar Rajasekaran. ipccc 2007: 402-409 [doi]

runs on WebDSL