Jean Louis Raisaro

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—In this paper, we propose privacy-enhancing technologies for personal use of the genomic data and analyze the tradeoff between genomic privacy and storage cost of the genomes. First, we highlight the potential privacy threats on the genomic data. Then, focusing specifically on a disease-susceptibility test, we develop a new architecture (between the(More)
In this paper, we propose privacy-enhancing technologies for medical tests and personalized medicine methods that use patients' genomic data. Focusing on genetic disease-susceptibility tests, we develop a new architecture (between the patient and the medical unit) and propose a "privacy-preserving disease susceptibility test" (PDS) by using homomorphic(More)
Geneticists prefer to store patients' aligned, raw genomic data, in addition to their variant calls (compact and summarized form of the raw data), mainly because of the immaturity of bioinformatic algorithms and sequencing platforms. Thus, we propose a privacy-preserving system to protect the privacy of aligned, raw genomic data. The raw genomic data of a(More)
—According to many scientists and clinicians, ge-nomics is the " next big thing " in the field of medicine. On one hand, decreasing costs in genome sequencing has been paving the way to better preventive and personalized medicine. On the other hand, genomic data also raises serious privacy concerns, as it is the ultimate identifier of an individual and it(More)
—We propose privacy-enhancing technologies for medical tests and personalized medicine methods, which utilize pa-tients' genomic data. Focusing specifically on a typical disease-susceptibility test, we develop a new architecture (between the patient and the medical unit) and propose a privacy-preserving algorithm by utilizing homomorphic encryption and(More)
—Recently, several solutions have been proposed to address the complex challenge of protecting individuals' genetic data during personalized medicine tests. In this short paper, we analyze different privacy threats and propose simple countermeasures for the generic architecture mainly used in the literature. In particular, we present and evaluate a new(More)
—In this paper, we propose privacy-enhancing technologies for medical tests and personalized medicine methods, which utilize patients' genomic data. First, we highlight the potential privacy threats on genomic data and the challenges of providing privacy-preserving algorithms. Then, focusing specifically on a typical disease-susceptibility test, we develop(More)
PURPOSE The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics. METHODS We genotyped 4,149 markers in HIV-positive individuals.(More)
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