New privacy threats in healthcare informatics: When medical records join the web

Fengjun Li, Jake Y. Chen, Xukai Zou, Peng Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, we study how patient privacy could be compromised from electronic health records (EHRs), especially with the help of today's information technologies. Current research on privacy protection is centralized around EHR: protecting patient information from being abused by authorized users or being accessed by unauthorized users. Limited efforts have been devoted to studying the attacks performed by manipulating information from external sources, or by joining information from multiple sources. Particularly, we show that (1) healthcare information could be collected by associating and aggregating information across multiple online sources including social networks, public records and search engines. Through attribution, inference and aggregation attacks, user identity and privacy are very vulnerable. (2) People are highly identifiable even when the attacker only possess inaccurate information. With real-world case study and experiments, we show that such attacks are valid and threatening. We claim that too much information has been made available electronic and available online that people are very vulnerable without effective privacy protection.

Original languageEnglish (US)
Title of host publicationProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery
Pages133-136
Number of pages4
ISBN (Electronic)9781605583020
StatePublished - Jan 1 2010
Event9th International Workshop on Data Mining in Bioinformatics, BIOKDD 2010, Held in Conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining - Washington, United States
Duration: Jul 25 2010Jul 28 2010

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Other

Other9th International Workshop on Data Mining in Bioinformatics, BIOKDD 2010, Held in Conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
CountryUnited States
CityWashington
Period7/25/107/28/10

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems

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