Evidence map›Paper›PMID 22010157›Full record

ArticleIEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society2012

Secure management of biomedical data with cryptographic hardware.

Mustafa Canim, Murat Kantarcioglu, Bradley Malin

Abstract read
In one paragraph

Article in IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Secure large-scale genome data storage and query.Computer methods and programs in biomedicine · 2018
    Article
  7. Private and Efficient Query Processing on Outsourced Genomic Databases.IEEE journal of biomedical and health informatics · 2017
    Article
  8. Article
  9. Article
  10. Privacy in the Genomic Era.ACM computing surveys · 2015
    Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mustafa CanimDepartment of Computer Science, University of Texas at Dallas, Richardson, TX 75083, USA. canim@utdallas.edu
Murat Kantarcioglu
Bradley Malin

Funding

Technologies to Enable Privacy in Biomedical DatabanksR01LM009989 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MALIN, BRADLEY A. · 2009 to 2014
$1.6M
NLM NIH HHS R01 LM009989NLM NIH HHS R01-LM009989
6 · The paper itself

Abstract

The biomedical community is increasingly migrating toward research endeavors that are dependent on large quantities of genomic and clinical data. At the same time, various regulations require that such data be shared beyond the initial collecting organization (e.g., an academic medical center). It is of critical importance to ensure that when such data are shared, as well as managed, it is done so in a manner that upholds the privacy of the corresponding individuals and the overall security of the system. In general, organizations have attempted to achieve these goals through deidentification methods that remove explicitly, and potentially, identifying features (e.g., names, dates, and geocodes). However, a growing number of studies demonstrate that deidentified data can be reidentified to named individuals using simple automated methods. As an alternative, it was shown that biomedical data could be shared, managed, and analyzed through practical cryptographic protocols without revealing the contents of any particular record. Yet, such protocols required the inclusion of multiple third parties, which may not always be feasible in the context of trust or bandwidth constraints. Thus, in this paper, we introduce a framework that removes the need for multiple third parties by collocating services to store and to process sensitive biomedical data through the integration of cryptographic hardware. Within this framework, we define a secure protocol to process genomic data and perform a series of experiments to demonstrate that such an approach can be run in an efficient manner for typical biomedical investigations.

Indexed as

Biomedical ResearchComputer SecurityDatabases, FactualDatabase Management SystemsElectronic Health Records

Identifiers

PMID22010157
PMCPMC4156282

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.