Privacy-Utility Feature Selection as a Privacy Mechanism in Collaborative Data Classification
Privacy-Utility Feature Selection as a Privacy Mechanism in Collaborative Data Classification
复制标题
隐私实用程序特征选择作为协作数据分类中的隐私机制
DOI：
10.1109/wetice.2017.15
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
F. Martinelli
中科院分区：
文献类型：
--
作者：
M. Alishahi;F. Martinelli
This paper presents a novel framework for privacy aware collaborative information sharing for data classification. Data holders participating in this information sharing system, for global benefits are interested to model a classifier on whole dataset, but are ready to share their own table of data if a certain amount of privacy is guaranteed. To address this issue, we propose a privacy mechanism based on privacy-utility feature selection, which by eliminating the most irrelevant set of features in terms of accuracy and privacy, guarantees the privacy requirements of data providers, whilst the data remain practically useful for classification. Due to the fact that the proposed trade-off metric is required to be exploited on whole dataset, a distributed secure sum protocol is utilized to protect information leakage in each site. The proposed approach is evaluated and validated through standard Tumor dataset.
