@inproceedings{f20427776b9f48efbbb05119c959aa6e,
title = "Privacy-Preserving Outsourcing of Data Mining",
abstract = "Data mining is gaining momentum in society due to the ever increasing availability of large amounts of data, easily gathered by a variety of collection technologies and stored via computer systems. Due to the limited computational resources of data owners and the developments in cloud computing, there has been considerable recent interest in the paradigm of data mining-as-a-service (DMaaS). In this paradigm, a company (data owner) lacking in expertise or computational resources outsources its mining needs to a third party service provider (server). Given the fact that the server may not be fully trusted, one of the main concerns of the DMaaS paradigm is the protection of data privacy. In this paper, we provide an overview of a variety of techniques and approaches that address the privacy issues of the DMaaS paradigm.",
keywords = "Outsourcing, Privacy, data mining",
author = "Anna Monreale and Wang, {Wendy Hui}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE 40th Annual Computer Software and Applications Conference, COMPSAC 2016 ; Conference date: 10-06-2016 Through 14-06-2016",
year = "2016",
month = aug,
day = "24",
doi = "10.1109/COMPSAC.2016.169",
language = "English",
series = "Proceedings - International Computer Software and Applications Conference",
pages = "583--588",
editor = "Ling Liu and Dejan Milojicic and Zhiyong Zhang and Zhiyong Zhang and Ahamed, {Sheikh Iqbal} and Hiroyuki Sato and Stevlio Cimato and William Claycomb and Sorel Reisman and Motonori Nakamura and Lung, {Chung Horng} and Mihhail Matskin",
booktitle = "Proceedings - 2016 IEEE 40th Annual Computer Software and Applications Conference Workshops, COMPSAC 2016",
}