[hinkley]

Yeah I thought of that too after posting. I think it comes down to how transparent the pool is with their data.

The obvious thing to do would be to tell everyone that my 500 GH/s pool is 400 GH/s, and reward everyone an 80% share on every hash. If you're sophisticated enough you might notice that my pool is mining blocks about 25% above what you'd expect, but how many data point do you need for that, and it's statistical, so I'll have runs of good or bad luck.

Another option is to dilute the pool of contributors, but again you might be able to detect that either I'm misreporting your hash rate, or the sum of all contributions doesn't line up.

Assuming I give you enough tools to figure any of this out.

[labawi]

If you report the pool's hash rate as lower, the users should demand a higher fair share, as they know their own hash rate.

Either way, if a user knows his hash rate, he can calculate expected earnings and their presumed share. You could fudge a bit, but go too much, especially on a large pool, and it will be apparent. There are probably lots of users doing calculations, willing to call you out.

[hinkley]

> If you report the pool's hash rate as lower

err, right. If you want to convince people they're getting a fair share, you have to downplay their contributions, and since they know what they did you have to make the pool bigger, not smaller. How long would it take to notice someone was fluffing the pool by 10%?

[RL_Quine]

The variance month to month is far higher than that for most pools. Nobody would ever notice, trust me.

[hinkley]

Yeah that’s what I meant by the statistical comment.

My hardest class in college was statistics, and mostly I learned that humans suck at them.

I was binging math videos recently and I got to one where one guy made a list of “random” heads or tails, and then the other guy guessed them and got like 60% right. He was disappointed because he often does better.

Humans, he asserted, will never write more than 3 (or was it 4?) heads in a row because they feel they aren’t random enough. And because if this, over half of the possible patterns are never seen.

Which is also why, when a test that’s failing 10% of the time, my coworker who thinks he just fixed it will run the new version five, ten times and claim victory... only for it to fail four times in a row the next day.