Grigorios Loukides

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Regulations in various countries permit the reuse of health information without patient authorization provided the data is "de-identified". In the United States, for instance, the Privacy Rule of the Health Insurance Portability and Accountability Act defines two distinct approaches to achieve de-identification; the first is <i>Safe Harbor</i>, which(More)
The publication of trajectory data opens up new directions in studying human behavior, but it is challenging to perform in a privacy-preserving way. This is mainly because, the identities of individuals, whose movement is recorded in the data, can be disclosed, even after removing identifying information. Existing works to anonymize trajectory data offer(More)
Transaction data about individuals are increasingly collected to support a plethora of applications, spanning from marketing to biomedical studies. Publishing these data is required by many organizations, but may result in privacy breaches, if an attacker exploits potentially identifying information to link individuals to their records in the published(More)
K-anonymisation is an approach to protecting privacy contained within a data set. A good k-anonymisation algorithm should anonymise a data set in such a way that private information contained within it is hidden, yet anonymised data is still useful in intended applications. Maximising both data usefulness and privacy protection in k-anonymisation is however(More)
OBJECTIVE De-identified clinical data in standardized form (eg, diagnosis codes), derived from electronic medical records, are increasingly combined with research data (eg, DNA sequences) and disseminated to enable scientific investigations. This study examines whether released data can be linked with identified clinical records that are accessible via(More)
<i>K</i>-anonymisation is an approach to protecting privacy contained within a dataset. A good <i>k</i>-anonymisation algorithm should anonymise a dataset in such a way that private information contained within it is hidden, yet the anonymised data is still useful in intended applications. However, maximising both data utility and privacy protection in(More)
The dissemination of Electronic Health Records (EHRs) can be highly beneficial for a range of medical studies, spanning from clinical trials to epidemic control studies, but it must be performed in a way that preserves patients' privacy. This is not straightforward, because the disseminated data need to be protected against several privacy threats, while(More)
Electronic medical record (EMR) systems have enabled healthcare providers to collect detailed patient information from the primary care domain. At the same time, longitudinal data from EMRs are increasingly combined with biorepositories to generate personalized clinical decision support protocols. Emerging policies encourage investigators to disseminate(More)