Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Design 2 - caveats and benefits - metadata #7

Open
ghost opened this issue Apr 29, 2020 · 0 comments
Open

Design 2 - caveats and benefits - metadata #7

ghost opened this issue Apr 29, 2020 · 0 comments

Comments

@ghost
Copy link

ghost commented Apr 29, 2020

With regard to: "There is a false-positive rate associated with cuckoo filters. This means that there is a chance (albeit a small one) that a user might get a notification that he is at risk even though he didn't encounter an infectious person." - I'd add that for population sizes (e.g. DE, NL or the US) the number is, in a naive implementation already 'ridiculously' small; i.e. 6 to 10 orders of magnitude smaller than general medical process error rates; while still preserving the < 20% of data volume win. If the health authorities would tune the filter daily (which is realistic; as it is a one-off effort) then you'd be hit around 15% if you assume a country > 10 Million and less 10 Billion inhabitants and COVID infection rates.

Secondly - and also with regard to "Only a single-bit of information can be transferred (whether the ID is reported or not)" -- it is quite common (or if you would want < 5% volume wins) to fetch; on a (potential false) positive - a partial (e.g. 1/1024th part) full fetch; which can include an arbitrary amount of metadata.

In that case; the cost/win relative to PACT and TCN is 100 - 5% + 1/1024th =~ 95% less bandwidth than the TCN case; while revealing around 10 to 30 bits of the full hash in the CF table and (in this example) 10 bits of the 256 bits (so less than the 30-50 in the CF) in the full set.

Or alternatively -if you want to reduce the subsequent fetches and have no issue with false positives; around 20% of the volume (80% saved) and 30-50 bits revealed.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

0 participants