TY - JOUR
T1 - A framework to preserve the privacy of electronic health data streams
AU - Kim, Soohyung
AU - Sung, Min Kyoung
AU - Chung, Yon Dohn
N1 - Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2013-022884).
PY - 2014/8
Y1 - 2014/8
N2 - The anonymization of health data streams is important to protect these data against potential privacy breaches. A large number of research studies aiming at offering privacy in the context of data streams has been recently conducted. However, the techniques that have been proposed in these studies generate a significant delay during the anonymization process, since they concentrate on applying existing privacy models (e.g., k-anonymity and l-diversity) to batches of data extracted from data streams in a period of time. In this paper, we present delay-free anonymization, a framework for preserving the privacy of electronic health data streams. Unlike existing works, our method does not generate an accumulation delay, since input streams are anonymized immediately with counterfeit values. We further devise late validation for increasing the data utility of the anonymization results and managing the counterfeit values. Through experiments, we show the efficiency and effectiveness of the proposed method for the real-time release of data streams.
AB - The anonymization of health data streams is important to protect these data against potential privacy breaches. A large number of research studies aiming at offering privacy in the context of data streams has been recently conducted. However, the techniques that have been proposed in these studies generate a significant delay during the anonymization process, since they concentrate on applying existing privacy models (e.g., k-anonymity and l-diversity) to batches of data extracted from data streams in a period of time. In this paper, we present delay-free anonymization, a framework for preserving the privacy of electronic health data streams. Unlike existing works, our method does not generate an accumulation delay, since input streams are anonymized immediately with counterfeit values. We further devise late validation for increasing the data utility of the anonymization results and managing the counterfeit values. Through experiments, we show the efficiency and effectiveness of the proposed method for the real-time release of data streams.
KW - Anonymization
KW - Health data stream
KW - Privacy
UR - http://www.scopus.com/inward/record.url?scp=84905270810&partnerID=8YFLogxK
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U2 - 10.1016/j.jbi.2014.03.015
DO - 10.1016/j.jbi.2014.03.015
M3 - Article
C2 - 24704716
AN - SCOPUS:84905270810
VL - 50
SP - 95
EP - 106
JO - Journal of Biomedical Informatics
JF - Journal of Biomedical Informatics
SN - 1532-0464
ER -