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Box 1 of the following paper has a nice definition for differential privacy in genomics sense (phenotypic differential privacy): http://www.cell.com/cell-systems/fulltext/S2405-4712(16)30121-1 “
Posts Tagged ‘privacy’
differential privacy
November 29, 2017Five Best File Encryption Tools
November 26, 2017GNU Privacy Guard v VeraCrypt – use w/ dropbox ? ease of install ?
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“VeraCrypt (Windows/OS X/Linux)
VeraCrypt is a fork of and a successor to TrueCrypt, which ceased development last year (more on them later.) The development team claims they’ve addressed some of the issues that were raised during TrueCrypt’s initial security audit, and like the original, it’s free, with versions available for Windows, OS X, and Linux. If you’re looking for a file encryption tool that works like and reminds you of TrueCrypt but isn’t exactly TrueCrypt, this is it. VeraCrypt supports AES (the most commonly used), TwoFish, and Serpent encryption ciphers, supports the creation of hidden, encrypted volumes within other volumes. Its code is available to review, although it’s not strictly open source (because so much of its codebase came from TrueCrypt.) The tool is also under constant development, with regular security updates and an independent audit in the planning stages (according to the developers.)”
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Is Genetic Privacy a Myth?
October 28, 2017QT:{{”
But it’s the very specificity of genomic data that threatens privacy. Although most genomic databases strip away any information linking a name to a genome, such information is very hard to keep anonymous. “I’m not convinced you can truly de-identify the data,” says Mark Gerstein, a Yale professor who studies large genetic databases and is a fierce privacy advocate. He is concerned about whether even the most cutting-edge protections can safeguard personal data. “I am not a believer that large-scale technical solutions or ‘super-encryption’ will solely work,” he says. “There also needs to be a process for credentialing the individuals who access this data.”
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Threats to privacy could multiply once there is an active market for genetic data. Wood speculates that it could be valuable to life insurance companies, which could use it to raise your premiums; or it could become a tool for those who want to prove or disprove paternity. White nationalist groups, who have become preoccupied with genetic testing, might find a way to weaponize the ancestry data the tests can show. It would not be the first time genetic information was used against a race or races. “Genetics has a very troubled history, from Darwin on,” says Yale’s Mark Gerstein.
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Yet Columbia’s Yaniv Erlich and others, including Church, fear differential privacy could compromise biomedical research, with smudged data making it harder to get clear results. Mark Gerstein at Yale believes that scientists would be better off testing hypotheses on small amounts of publicly available but pure data, even if it’s not representative of the overall population, rather than using larger quantities of imperfect data.
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Is Genetic Privacy a Myth?
http://protomag.com/articles/genetic-privacy-myth
Genetic tests and genome sequencing are generating terabytes of sensitive private data. How can they be kept safe?
German activities on RNA privacy
October 21, 2017http://www.mhumbert.com/publications/oakland17.pdf
Identifying Personal DNA Methylation Profiles by Genotype Inference
Michael Backes⇤, Pascal Berrang⇤, Matthias Bieg†, Roland Eils†‡, Carl Herrmann†‡, Mathias Humbert⇤, Irina Lehmann§
Re-Identification of Individuals in Genomic Data-Sharing Beacons via Allele Inference | bioRxiv
October 21, 2017https://www.biorxiv.org/content/early/2017/10/09/200147
higher order markov to predict snps
Backed into a corner, Uber allows users to opt out of ‘always on’ location tracking – The Verge
September 25, 2017Artificial intelligence just made guessing your password a whole lot easier
September 22, 2017#AI just made guessing your password…easier
http://www.ScienceMag.org/news/2017/09/artificial-intelligence-just-made-guessing-your-password-whole-lot-easier rather Number cracked raises #security/#privacy concerns HT @Rozowsky
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The new study aimed to speed this up by applying deep learning, a brain-inspired approach at the cutting edge of AI. Researchers at Stevens Institute of Technology in Hoboken, New Jersey, started with a so-called generative adversarial network, or GAN, which comprises two artificial neural networks. A “generator” attempts to produce artificial outputs (like images) that resemble real examples (actual photos), while a “discriminator” tries to detect real from fake. They help refine each other until the generator becomes a skilled counterfeiter.
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We’re committed to your security
September 17, 2017https://www.equifaxsecurity2017.com/
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As you may have heard, Equifax, one of the three largest credit monitoring bureaus in the U.S., announced a data breach at the company that may have affected 143 million U.S. consumers. The breach included social security numbers, birth dates, addresses, credit card numbers as well as other personal information.
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Sampling DNA From a 1,000-Year-Old Illuminated Manuscript
September 16, 2017Sampling DNA From a 1K-Year-Old…Manuscript
https://www.theAtlantic.com/science/archive/2017/08/the-secret-life-of-illuminated-manuscripts-as-told-in-dna/536172/ As reported from a unsubmitted preprint. Pot. #privacy implications
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Remarkably, the authors say they extracted all this DNA without destroying even a tiny piece of parchment. All they needed were the crumbs from rubbing the book with erasers, which conservationists routinely use to clean manuscripts. The authors report their findings in a preprint that has not yet been peer-reviewed, though they plan to submit it to a scientific journal.”
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Identity Thieves Hijack Cellphone Accounts to Go After Virtual Currency
September 5, 2017Identity Thieves Hijack Cellphone Accounts to Go After Virtual
Currency https://www.nytimes.com/2017/08/21/business/dealbook/phone-hack-bitcoin-virtual-currency.html Problematic #privacy loophole w/ #2factor
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“Hackers have discovered that one of the most central elements of online security — the mobile phone number — is also one of the easiest to steal.
In a growing number of online attacks, hackers have been calling up Verizon, T-Mobile U.S., Sprint and AT&T and asking them to transfer control of a victim’s phone number to a device under the control of the hackers.
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