A framework to preserve the privacy of electronic health data streams

Soohyung Kim, Min Kyoung Sung, Yon Dohn Chung

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)95-106
Number of pages12
JournalJournal of Biomedical Informatics
Publication statusPublished - 2014 Aug


  • Anonymization
  • Health data stream
  • Privacy

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics


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