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Presentation
Privacy Preserving Boosting in the Cloud with Secure Half-Space Queries
Proceedings of the 2012 ACM Conference on Computer and Communications Security
  • Shumin Guo, Wright State University - Main Campus
  • Keke Chen, Wright State University - Main Campus
Document Type
Conference Proceeding
Publication Date
10-1-2012
Abstract

This paper presents a preliminary study on the PerturBoost approach that aims to provide efficient and secure classifier learning in the cloud with both data and model privacy preserved.

Comments

Presented at the 2012 ACM Conference on Computer and Communications Security, Raleigh, NC, October 16-18, 2012.

DOI
10.1145/2382196.2382315
Citation Information
Shumin Guo and Keke Chen. "Privacy Preserving Boosting in the Cloud with Secure Half-Space Queries" Proceedings of the 2012 ACM Conference on Computer and Communications Security (2012) p. 1031 - 1033 ISSN: 9781450316514
Available at: http://works.bepress.com/keke_chen/8/