from Hacker News

How to generate keys from facial images and keep privacy at the same time (2018) [pdf]

by legionof7 on 4/26/20, 10:18 PM with 7 comments

• by nullc on 4/27/20, 8:25 AM

  The minisketch library I worked on can be used for near optimal (in the sense of information leak) error correction for "set like" features:

  https://github.com/sipa/minisketch/

  Our application is for communications efficient set reconciliation to convert Bitcoin's quadratic-overhead transaction gossip protocol (O(txn*peers)) to effectively linear (O(txn)), though the primary academic work that our work was based on were concerned with fuzzy extractors for privacy preserving (and encryption key generating) biometrics.

• by O81s1iiCHUP9 on 4/26/20, 11:53 PM

  Hmm...

  This is old research, which seems to be a recreation of the work of Sutcu et al. among others.

  I did my masters thesis on this.

• by barbegal on 4/27/20, 10:09 AM

  I feel like the ability for this method to work well depends on the methodology of taking the enrollment and the subsequent key-generation images. If you take them using the same poses, with the same camera and lighting within a few hours of each other then this method will work extremely well [1]. I really doubt it generalizes to the case of using it with a laptop webcam in any location with different lighting.

  But maybe I am wrong, maybe there are enough bits of information in a randomly lit image of a face.

  [1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2898524/

• by 1cvmask on 4/26/20, 11:33 PM

  Has IBM built a product around this? I don’t know of one.

  Or is the research for patent purposes only?

• by WorldPeas on 4/27/20, 3:59 PM

  Someone at the University of Haifa has a sense of humor