Late Nov we attempted mock IBS baiting hack. We used only artificial kits (for targets and baits) & restricted it to the `research’ branch of GEDmatch (so we never interacted w. other people’s data nor violated T&C). We also verified this plan with UC Davis IRB and GEDMatch 5/n
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Our bait kits (B1 & B2) had het. & missing genos around target to bait IBS caller. We could tell if target was homozy. by which bait it IBS matched (eg. T1=B1 but not B2), & if it was heterozy if matched both baits (T2 vs B1 & B2). Image compiled from GEDmatch browser 6/npic.twitter.com/EKlK2cl1ss
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This baiting worked easily across four targeted regions on chromosome 22. We set up our baits to not match outside these regions & we saw no other IBS in genome-wide. Baiting could likely easily be extended to extract more genotypes genome-wide 7/npic.twitter.com/mSyAdfigqa
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Note that this only needs GEDmatch to return IBS locations to extract genotypes, & doesnt need images. The images reveal even more info. GEDmatch seems to have jittered SNP positions (trying to block
@_peterney-style attack?) but incomp genos in our baits are still visible 8/n0 proslijeđenih tweetova 0 korisnika označava da im se sviđaPrikaži ovu nit -
Interesting. Can you please elaborate on those jitters? Does it make the Ney et all attack using images impossible?
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The jitter is visible in our Fig5, left side---the red lines that prevent the IBS calls in the second and 5th bars should line up exactly, but they don't.
@_peterney can correct me here, but my understanding is that this would hamper the exact attack they described, but...1 reply 0 proslijeđenih tweetova 2 korisnika označavaju da im se sviđa -
Odgovor korisnicima @DocEdge85 @ShaiCarmi i sljedećem broju korisnika:
...I am not sure how robust a solution it is. E.g. one workaround would be to do a hybrid of baiting and Ney image analysis. In baiting, incomp. homs. produce red lines against a yellow/green background, which would let one place that coordinate confidently
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Yes, the exact algorithm as described in the paper breaks with jittering.
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Odgovor korisnicima @_peterney @DocEdge85 i sljedećem broju korisnika:
There is an assumption in the algorithm that if you compare two kits, containing the identical SNPs, against a target kit that the each pixel will correspond to the same SNP in both comparisons. This assumptions used to be true but isn't true with jittering.
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Odgovor korisnicima @_peterney @DocEdge85 i sljedećem broju korisnika:
However, I view jittering as more of a stop-gap solution rather than a long term fix. As
@DocEdge85 &@Graham_Coop allude, it may possible to "re-synchronize" the visualizations to undo the jittering. This is similar to autocorrelating that is done in signal processing.0 proslijeđenih tweetova 2 korisnika označavaju da im se sviđa
I'm pretty skeptical that any SNP-level visualizations are secure against these types of information leakage attacks. They just reveal too much information about the target kit. You may not even have to use artificial kits, although that would make things more complicated.
Čini se da učitavanje traje već neko vrijeme.
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