[Cryptech Tech] RNG test tools wiki page

[Benedikt Stockebrand]

Hi Bernd and list,

Bernd Paysan <bernd at net2o.de> writes:

> Am Donnerstag, 31. Juli 2014, 13:15:18 schrieb Benedikt Stockebrand:
>> Bernd Paysan <bernd at net2o.de> writes:
>> > IMHO, dieharder -a should collect all the results and do a chi-square
>> > tests on them, because if the data is random, and the weighting is
>> > correct, the results should all be distributed with a known distribution.
>> 
>> No, that's not a good idea.  If any single test fails it means that it
>> has with high likelyhood discovered some sort of pattern or
>> nonrandomness in the input.  But that doesn't mean it will also be
>> discovered by other tests.
>
> If a single test fails with a 0.1% likelyhood, and you have a total number of 
> tests that is already >100, this is nothing to worry too much about. Take an 
> independent data sample, and test again - if it now fails twice with the same 
> test, the likelyhood is 1ppm, and you should start to worry.

that's basically what the "-Y 1" option for dieharder does, but for a
single test, not the entire test suite.

>> As a simplified example: If you had one test for bit bias (what ent
>> calls "entropy") and a second for correlation between bits 8 bits apart
>> (which might be interesting for a bytewise generator) then it takes two
>> different kinds of patterns overlaid in the input to make both tests
>> fail.
>
> When you have tests which test independent properties, then you would expect 
> to have the results stochastically independent, as well.  [...]

That's what I meant.

> There are tests in dieharder which are sensitive to very similar things, and 
> will have corellated results.  Putting these tests together into a too tough 
> meta-test wouldn't be a good idea. Putting independent tests (tests which test 
> different properties of randomness) into a meta-test IMHO is good.

I can't quite follow here: If one test shows that there is a significant
bit bias, why would I combine it with one testing for correlation with a
bit distance of 8, and therefore dilute the result?

> You'll also expect that the same tests run on an independent data sample will 
> have independent results.

Sorry, maybe I'm just too tired (and still struggling with a cold from
that polar airport air...), but what exactly do you mean with that?


Cheers,

    Benedikt

-- 
Benedikt Stockebrand,                   Stepladder IT Training+Consulting
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