標題: A Scalable Privacy Preserving System for Open Data
作者: Yeh, Chao-Chun
Wang, Pang-Chieh
Pan, Yu-Hsuan
Kao, Ming-Chih
Huang, Shih-Kun
資訊工程學系
資訊技術服務中心
Department of Computer Science
Information Technology Services Center
關鍵字: open data;big data;privacy preserving;K-anonymity
公開日期: 1-一月-2016
摘要: The citizen considers that data source collecting by the government can be released for more diversity usage. However, to archive the open data dream, sensitive data potentially could be published after the proper privacy preserving processing. In this paper, we present a scalable privacy preserving system for open/big data which leverages K-anonymity algorithm and Hadoop framework. We use an experiment data (i.e., 10 TB) to show our system can handle the high-volume data when increasing the system resource. It is an essential factor for the Government to publish the data with privacy preserving processing.
URI: http://dx.doi.org/10.1109/ICS.2016.68
http://hdl.handle.net/11536/146728
DOI: 10.1109/ICS.2016.68
期刊: 2016 INTERNATIONAL COMPUTER SYMPOSIUM (ICS)
起始頁: 312
結束頁: 317
顯示於類別:會議論文