Send help plz lol

Feel like we're back in WW2. Breaking codes over here. Channeling my inner Turing

Some are trying to make it this whole thing take an entire year

The report mentions using iterative clustering with DBSCAN.Clustering is an algorithm that forms multiple clusters based on similarity. When filtering for Sybil attacks, accuracy is crucial. Grouping based on a few similar metrics, such as source chain interaction count, target chain interaction count, and total transaction value, is very risky. Just because these metrics are similar, does it make sense to cluster and identify them as Sybil attacks? I don't think so. This algorithm is not suitable for identifying Sybil attacks and is likely to produce a high rate of false positives. This report misses more important methods and is ultimately useless.

I’d like someone to show some examples of false positives vs loosely say it’s possible that there could be false positives

But you guys put lots of single wallet user as Sybil in your preliminary stage...... example me offcourse, I m ready to proof anything still no resonse from team ....I can provide access to all devices in my house , my government id , and my whole networth is in that wallet.

Y don’t you defer this validation process to experts, would prob be a lot more reliable

Dear @PrimordialAA ,I found this report: I found that it was reported because an unknown address sent me a token that I don’t know what it is: neo. 0x74E949a07994121856fa45cbEb7dECe2BF721CC9 sent neo tokens to 160 addresses. I don’t know what this is.

Bryan can you please look at this?

x-ray of Sybil address? 🤣

Please review this one and you can see matching tx are from dfk game who was playing that game one address is mine and its full of false positive addresses