17:01:32 24 hours from now there will be an MRL meeting in this channel: 17:01:32 https://github.com/monero-project/meta/issues/624 17:40:38 Rucknium[m]: so your CCS is, as far as you can tell, a way to make Monero resistant to statistical analysis? 17:50:35 Inge: Yes, a particular type of statistical analysis involving the ages of ring members. 17:57:01 The issue is this: The age of all ring members is known. The ring members each come from a particular identifiable block, and each block was mined at a particular point in time. 17:59:53 So you cannot just have the decoy selection algorithm select decoy ring members willy-nilly. If, for instance, you always select decoys from more than a year ago, and users are spending outputs that are less than a year old, then the "true spend" input can be identified. That would make Monero transactions somewhat traceable, in a sense. 18:01:06 The best thing to do is to employ a probability density function that exactly mimics the "real spend" age distribution, since then decoys look like real spends in pretty much every way. 18:02:04 To the extend that there is a substantial difference between the real spend age distribution and the decoy distribution, user privacy is somewhat harmed. 18:03:05 So the purpose of the research is to construct a probability density function for the decoy selection algorithm that is as close as possible to the real spend distribution so that real spends are as difficult to identify as possible. 18:57:40 i am still flummoxed regarding how we can know the real spend distribution 18:59:16 If you have enough data points, like any other distribution: subtract the synthetic distribution from the observed one. 19:01:31 but it can change over time... hence Rucknium[m] 's adaptive thing they mentioned .... hrmmmm 19:10:08 bridgerton is the bot handling the matrix-discord bridge :D 21:40:31 moneromooo: and how can one get the synthetic distribution? 21:42:42 wallet2.cpp, grep for gamma. 21:43:10 Also described in Moser et al. 21:43:21 There might be a URL or title in the source. 21:43:46 Though the exact distribution is in the code, as shown by jberman[m].