Proxy-secure computation model: application to k-means clustering implementation, analysis and improvements

Official URL: http://192.168.1.20/record=b1302893 (Table of Contents)

Distributed privacy preserving data mining applications, where data is divided among several parties, require high amounts of network communication. In order to overcome this overhead, we propose a scheme that reduces remote computations in distributed data mining applications into local computations on a trusted hardware. Cell BE is used to realize the trusted hardware acting as a proxy for the parties. We design a secure two-party computation protocol that can be instrumental in realizing non-colluding parties in privacy-preserving data mining applications. Each party is represented with a signed and encrypted thread on a separate core of Cell BE running in an isolated mode, whereby its execution and data are secured by hardware means. Our implementations and experiments demonstrate that a significant speed up is gained through the new scheme. It is also possible to increase the number of non-colluding parties on Cell BE, which extends the proposed technique to implement most distributed privacy-preserving data mining protocols proposed in literature that require several non-colluding parties.