3,180 research outputs found
Privacy in the Genomic Era
Genome sequencing technology has advanced at a rapid pace and it is now
possible to generate highly-detailed genotypes inexpensively. The collection
and analysis of such data has the potential to support various applications,
including personalized medical services. While the benefits of the genomics
revolution are trumpeted by the biomedical community, the increased
availability of such data has major implications for personal privacy; notably
because the genome has certain essential features, which include (but are not
limited to) (i) an association with traits and certain diseases, (ii)
identification capability (e.g., forensics), and (iii) revelation of family
relationships. Moreover, direct-to-consumer DNA testing increases the
likelihood that genome data will be made available in less regulated
environments, such as the Internet and for-profit companies. The problem of
genome data privacy thus resides at the crossroads of computer science,
medicine, and public policy. While the computer scientists have addressed data
privacy for various data types, there has been less attention dedicated to
genomic data. Thus, the goal of this paper is to provide a systematization of
knowledge for the computer science community. In doing so, we address some of
the (sometimes erroneous) beliefs of this field and we report on a survey we
conducted about genome data privacy with biomedical specialists. Then, after
characterizing the genome privacy problem, we review the state-of-the-art
regarding privacy attacks on genomic data and strategies for mitigating such
attacks, as well as contextualizing these attacks from the perspective of
medicine and public policy. This paper concludes with an enumeration of the
challenges for genome data privacy and presents a framework to systematize the
analysis of threats and the design of countermeasures as the field moves
forward
Systematizing Genome Privacy Research: A Privacy-Enhancing Technologies Perspective
Rapid advances in human genomics are enabling researchers to gain a better
understanding of the role of the genome in our health and well-being,
stimulating hope for more effective and cost efficient healthcare. However,
this also prompts a number of security and privacy concerns stemming from the
distinctive characteristics of genomic data. To address them, a new research
community has emerged and produced a large number of publications and
initiatives.
In this paper, we rely on a structured methodology to contextualize and
provide a critical analysis of the current knowledge on privacy-enhancing
technologies used for testing, storing, and sharing genomic data, using a
representative sample of the work published in the past decade. We identify and
discuss limitations, technical challenges, and issues faced by the community,
focusing in particular on those that are inherently tied to the nature of the
problem and are harder for the community alone to address. Finally, we report
on the importance and difficulty of the identified challenges based on an
online survey of genome data privacy expertsComment: To appear in the Proceedings on Privacy Enhancing Technologies
(PoPETs), Vol. 2019, Issue
Routes for breaching and protecting genetic privacy
We are entering the era of ubiquitous genetic information for research,
clinical care, and personal curiosity. Sharing these datasets is vital for
rapid progress in understanding the genetic basis of human diseases. However,
one growing concern is the ability to protect the genetic privacy of the data
originators. Here, we technically map threats to genetic privacy and discuss
potential mitigation strategies for privacy-preserving dissemination of genetic
data.Comment: Draft for comment
Learning Character Strings via Mastermind Queries, with a Case Study Involving mtDNA
We study the degree to which a character string, , leaks details about
itself any time it engages in comparison protocols with a strings provided by a
querier, Bob, even if those protocols are cryptographically guaranteed to
produce no additional information other than the scores that assess the degree
to which matches strings offered by Bob. We show that such scenarios allow
Bob to play variants of the game of Mastermind with so as to learn the
complete identity of . We show that there are a number of efficient
implementations for Bob to employ in these Mastermind attacks, depending on
knowledge he has about the structure of , which show how quickly he can
determine . Indeed, we show that Bob can discover using a number of
rounds of test comparisons that is much smaller than the length of , under
reasonable assumptions regarding the types of scores that are returned by the
cryptographic protocols and whether he can use knowledge about the distribution
that comes from. We also provide the results of a case study we performed
on a database of mitochondrial DNA, showing the vulnerability of existing
real-world DNA data to the Mastermind attack.Comment: Full version of related paper appearing in IEEE Symposium on Security
and Privacy 2009, "The Mastermind Attack on Genomic Data." This version
corrects the proofs of what are now Theorems 2 and 4
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