@inproceedings{91b4b3b1d75a429b9df630ff9ee03e5e,
title = "Privacy-Preserving Deep Learning Computation for Geo-Distributed Medical Big-Data Platforms",
abstract = "This paper proposes a distributed deep learning framework for privacy-preserving medical data training. In order to avoid patients' data leakage in medical platforms, the hidden layers in the deep learning framework are separated and where the first layer is kept in platform and others layers are kept in a centralized server. Whereas keeping the original patients' data in local platforms maintain their privacy, utilizing the server for subsequent layers improves learning performance by using all data from each platform during training.",
keywords = "Deep Learning, Medical Big Data, Privacy Preserving",
author = "Joohyung Jeon and Junhui Kim and Joongheon Kim and Kwangsoo Kim and Aziz Mohaisen and Kim, {Jong Kook}",
note = "Funding Information: ACKNOWLEDGMENT This work was supported by IITP (2017-0-00068 and 2018-0-00170) and also by National Research Foundation of Korea (2016R1C1B1015406 and 2017R1A4A1015675). J. Kim is a corresponding author (e-mail: joongheon@gmail.com). Publisher Copyright: {\textcopyright} 2019 IEEE.; 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume, DSN-S 2019 ; Conference date: 24-06-2019 Through 27-06-2019",
year = "2019",
month = jun,
doi = "10.1109/DSN-S.2019.00007",
language = "English",
series = "Proceedings - 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume, DSN-S 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3--4",
booktitle = "Proceedings - 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume, DSN-S 2019",
}