Routes for breaching and protecting genetic privacy

Erlich, Yaniv; Narayanan, Arvind

doi:10.1038/nrg3723

Cited by 338 publications

(157 citation statements)

References 114 publications

(116 reference statements)

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“…So far, we have neither informally nor formally reported evidence for data breaches, apart from the proof of principle that reidentification is feasible in some cases with considerable effort. 14,62 Hence, patients' weighing of scientific benefits over the risk to their privacy seems a well-considered judgment. Unless we experience evidence for serious data breaches, rigid terms of data protection would therefore constitute paternalism over patient preferences and an unjustified obstruction to research.…”

Section: Data Sharing and Privacy Protectionmentioning

confidence: 99%

Stakeholders’ perspectives on biobank-based genomic research: systematic review of the literature

et al. 2015

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The success of biobank-based genomic research is widely dependent on people's willingness to donate their tissue. Thus, stakeholders' opinions should be considered in the development of best practice guidelines for research and recruiting participants. We systematically analyzed the empirical literature describing different stakeholders' views towards ethical questions with regard to type of consent, data sharing and return of incidental findings. Patients are more open to one-time general consent than the public. Only a small proportion desires recontact if the research aim changed. A broad consent model would prevent only a small proportion of patients from participating in research. Although professionals are concerned about a risk of reidentification, patients and the public support data sharing and find that the benefit of research outweighs the potential risk of reidentification. However, they desire detailed information about the privacy protection measures. Regarding the return of incidental findings, the public and professionals focus on clinically actionable results, whereas patients are interested in receiving as much information as possible. For professionals, concrete guidelines that help managing the return of incidental findings should be warranted. For this it would be helpful addressing the different categories -actionable, untreatable and inheritable diseases -upfront with patients and public. European Journal of Human Genetics (2015Genetics ( ) 23, 1607Genetics ( -1614 doi:10.1038/ejhg.2015; published online 4 March 2015 INTRODUCTIONTechnical advances in whole-genome sequencing enable the identification of genomic variations involved in the development of diseases, such as acquired mutations that are causally linked to cancer. 1,2 Improvements in disease prevention as well as diagnostic and therapeutic strategies may eventually lead to more precise, individually stratified health care. As most diseases are complex, which means that they are caused by multiple genomic factors, research is often based on large numbers of samples representing large numbers of individuals to arrive at statistically significant conclusions. In addition, genetic susceptibility alone is not sufficient to induce a complex disease; the causes also include different lifestyle and environmental factors. Therefore, to study complex diseases the interplay of all of these factors has to be considered. An efficient tool to achieve this is the creation of biobanks. Biobanks are defined as organized collections of human biological specimens comprised of cells, tissues, blood or DNA, which could be linked to clinical data and detailed individual lifestyle. Biobanks vary with respect to types and sources of samples and size, as well as research focus. Biobanks can be disease-specific or population-based, ranging from small collections to large-scale repositories. [3][4][5][6][7] Linking biological materials to personal data for enabling biobankbased genomic research raises several ethical questions that are currently debated. Th...

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Section: Data Sharing and Privacy Protectionmentioning

confidence: 99%

Stakeholders’ perspectives on biobank-based genomic research: systematic review of the literature

et al. 2015

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“…In spite of these works about differentially private genomic data, Fredrikson et al [35] demonstrate an unsatisfactory tradeoff between privacy and utility in an end-to-end case study of personalized warfarin dosing. A similar unsatisfactory result in an association study is also mentioned by Erlich and Narayanan [36].…”

Section: Related Workmentioning

confidence: 69%

GenoGuard: Protecting Genomic Data against Brute-Force Attacks

Huang

Ayday

Fellay

et al. 2015

2015 IEEE Symposium on Security and Privacy

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Abstract-Secure storage of genomic data is of great and increasing importance. The scientific community's improving ability to interpret individuals' genetic materials and the growing size of genetic database populations have been aggravating the potential consequences of data breaches. The prevalent use of passwords to generate encryption keys thus poses an especially serious problem when applied to genetic data. Weak passwords can jeopardize genetic data in the short term, but given the multidecade lifespan of genetic data, even the use of strong passwords with conventional encryption can lead to compromise.We present a tool, called GenoGuard, for providing strong protection for genomic data both today and in the long term. GenoGuard incorporates a new theoretical framework for encryption called honey encryption (HE): it can provide information-theoretic confidentiality guarantees for encrypted data. Previously proposed HE schemes, however, can be applied to messages from, unfortunately, a very restricted set of probability distributions. Therefore, GenoGuard addresses the open problem of applying HE techniques to the highly non-uniform probability distributions that characterize sequences of genetic data.In GenoGuard, a potential adversary can attempt exhaustively to guess keys or passwords and decrypt via a bruteforce attack. We prove that decryption under any key will yield a plausible genome sequence, and that GenoGuard offers an information-theoretic security guarantee against messagerecovery attacks. We also explore attacks that use side information. Finally, we present an efficient and parallelized software implementation of GenoGuard.

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“…To protect privacy, de-identification methods for healthcare data should be developed. In addition, recent privacy preserving data mining methods including differential privacy or homomorphic encryption should be applied to healthcare data [42].…”

Section: Resultsmentioning

confidence: 99%

Status and Direction of Healthcare Data in Korea for Artificial Intelligence

Park

Shin

2017

Hanyang Med Rev

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Predicting temporal patterns across various domains poses significant challenges due to their nuanced and often nonlinear trajectories. To address this challenge, prediction frameworks have been continuously refined, employing data-driven statistical methods, mathematical models, and machine learning. Recently, as one of the challenging systems, shared transport systems such as public bicycles have gained prominence due to urban constraints and environmental concerns. Predicting rental and return patterns at bicycle stations remains a formidable task due to the system's openness and imbalanced usage patterns across stations. In this study, we propose a deep learning framework to predict rental and return patterns by leveraging cartogram approaches. The cartogram approach facilitates the prediction of demand for newly installed stations with no training data as well as long-period prediction, which has not been achieved before. We apply this method to public bicycle rentaland-return data in Seoul, South Korea, employing a spatial-temporal convolutional graph attention network. Our improved architecture incorporates batch attention and modified node feature updates for better prediction accuracy across different time scales. We demonstrate the effectiveness of our framework in predicting temporal patterns and its potential applications.

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Routes for breaching and protecting genetic privacy

Cited by 338 publications

References 114 publications

Stakeholders’ perspectives on biobank-based genomic research: systematic review of the literature

Stakeholders’ perspectives on biobank-based genomic research: systematic review of the literature

GenoGuard: Protecting Genomic Data against Brute-Force Attacks

Status and Direction of Healthcare Data in Korea for Artificial Intelligence

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