[Cryptography] Is Ron right on randomness

dj at deadhat.com dj at deadhat.com
Sat Nov 26 10:42:04 EST 2016


>>
>> No, the above #2 is not accurate. It does matter how good your entropy
>> source is. The leftover hash lemma gives you the expression for the
>> amount
>> of entropy you can extract from entropy sources - but doesn't tell you
>> how
>> and for the real constructions the answer is worse. Subsequent papers
>> given bounds for certain specific extractors. This can be be summarized
>> as
>> the 0.5 limit. If your input data has less that 0.5 bits of entropy per
>> bit of data, your extractor is swimming upstream slower than the stream
>> is
>> moving downstream.
>
> Reference please?  Because this would be news to me (and, I think, a lot
> of other people as well).
>

This is extractor theory which I'm by no means an expert in, but I did
just come back from the COST-IACR School on Randomness in Cryptography
(https://eventum.upf.edu/5484/speakers/cost-iacr-school-on-randomness-in-cryptography.html),
which was a week long set of lectures mostly on the current state of
extractor theory from the professors who developed it so I'm feeling
pretty clued in right now - that will pass.

I've posted these before on this list, but the previous discussions
suggest they are not widely read. In particular the

[a]
Start at the start, you can't encrypt one bit from in the presence of a
weak source.
https://www.cs.nyu.edu/courses/spring06/G22.3220-001/pinkas.pdf
So you're going to have to do something else.

[b] But you can still do crypto:
https://people.csail.mit.edu/ronitt/COURSE/S08/drafts/22.pdf

[c]
The utility of your extracted random numbers depend on what you plan to do
with them:
https://www.cs.nyu.edu/~dodis/ps/weak.pdf

[d]
Bounds for CBC-MAC and HMAC. AKA the 0.5 Limit.
But those bounds are in terms of computational bounds on the adversary,
not min entropy:
https://www.cs.nyu.edu/~dodis/ps/hmac.pdf

[e]
Last week's randomness school had a strong focus on developing chain rules
for conditional entropy under various entropy models (Min, Shannon,
Guessing, Collision, HILL, metric, metric*) but since the authors of these
paper were lecturing, I think I actually understood it. There are a lot of
papers to read, but this survey paper is a good place to start:
https://www.cs.bu.edu/~reyzin/papers/entropy-survey.pdf

[f]
Multiple input extractors help you get past the 0.5 limit:
https://www.cs.nyu.edu/~dodis/ps/2-ext.pdf
http://www.boazbarak.org/Papers/msamples.pdf

[f]
Extractors have different bounds when you consider the entropy against
computationally bounded adversaries (that's us!) the general case being
HILL entropy.
https://eprint.iacr.org/2012/466.pdf

Is there a chain rule from which you can derive the entropy? It's an open
question, but this paper has counterexamples under some simple
assumptions, which is a no vote:
https://eprint.iacr.org/2014/678.pdf
There were other cryptographers present who were not so sure.

There is a lot lot more, but these are good starting points.

DJ







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