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The collection and sharing of person-specific biospecimens has raised significant questions regarding privacy. In particular, the question of identifiability, or the degree to which materials stored in biobanks can be linked to the name of the individuals from which they were derived, is under scrutiny. The goal of this paper is to review the extent to(More)
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)
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)
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)
The proliferation of GPS-enabled devices (e.g., smartphones and tablets) and location-based social networks has resulted in the abundance of trajectory data. The publication of such data opens up new directions in analyzing, studying and understanding human behavior. However, it should be performed in a privacy-preserving way, because the identities of(More)
Transaction data, such as market basket or diagnostic data, contain sensitive information about individuals. Such data are often disseminated widely to support analytic studies. This raises privacy concerns, as the confidentiality of individuals must be protected. Economization is an established methodology to protect transaction data, which can be applied(More)
Genome-wide association studies (GWAS) facilitate the discovery of genotype-phenotype relations from population-based sequence databases, which is an integral facet of personalized medicine. The increasing adoption of electronic medical records allows large amounts of patients' standardized clinical features to be combined with the genomic sequences of(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)
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)