An Architecture for High-Performance, Privacy-Preserving Data Mining

You can download an executive summary of the dissertation here .

For a preview of the dissertation's content, consult the following references:

• Here is a paper accepted to DMIN 2009 in Las Vegas, about APHID: (Architecture for Private and High-performance Integrated Data mining), the main architecture to be discussed in the dissertation.  A greatly expanded version of this is almost finished and will be sent to the journal Future Generation Computer Systems.
  
• Here is a journal paper currently under review at Data and Knowledge Engineering, which comprehensively discusses the privacy-preserving Probabilistic Nerual Network, that provided much of the motivation for developing the dissertation's framework (APHID)
• A short discussion of the privacy-preserving PNN was also published at the International Joint Conference on Neural Networks 2007, with the paper available here (it is superceded by the paper given above)