Result Integrity Verification of Outsourced Bayesian Network Structure Learning

Ruilin Liu, Wendy Hui Wang, Changhe Yuan

Abstract

There has been considerable recent interest in the data- mining-as-a-service paradigm: the client that lacks computational resources outsources his/her data and data mining needs to a third-party service provider. One of the security issues of this outsourcing paradigm is how the client can verify that the service provider indeed has returned correct data mining results. In this paper, we focus on the problem of result verification of outsourced Bayesian network (BN) structure learning. We consider the untrusted service provider that intends to return wrong BN structures. We develop three efficient probabilistic verification approaches to catch the incorrect BN structure with high probability and cheap overhead. Our experimental results demonstrate that our verification methods can capture wrong BN structure effectively and efficiently.

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Bibtex

@INPROCEEDINGS{Liu14result,
author = {Ruilin Liu, Wendy Hui Wang, Changhe Yuan},
title = {Result Integrity Verification of Outsourced Bayesian Network Structure Learning},
booktitle = {In Proceedings of the 2014 SIAM International Conference on Data Mining (SDM-14)},
address = {Philadephia, Pennsylvania},
year = {2014}
}