combining entropy

John Denker jsd at av8n.com
Tue Oct 28 15:09:04 EDT 2008


On 10/28/2008 09:43 AM, Leichter, Jerry wrote:

> | We start with a group comprising N members (machines or 
> | persons).  Each of them, on demand, puts out a 160 bit 
> | word, called a "member" word.  We wish to combine these 
> | to form a single word, the "group" word, also 160 bits 
> | in length.
> This isn't enough.  Somehow, you have to state that the values emitted
> on demand in any given round i (where a round consists of exactly one
> demand on all N member and produces a single output result) cannot
> receive any input from any other members.  Otherwise, if N=2 and member
> 0 produces true random values that member 1 can see before it responds
> to the demand it received, then member 1 can cause the final result to
> be anything it likes.


Perhaps an example will make it clear where I am coming
from.  Suppose I start with a deck of cards that has been 
randomly shuffled.  It can provide log2(52!) bits of 
entropy.  That's a little more than 225 bits.  Now suppose 
I have ten decks of cards all arranged alike.  You could 
set this up by shuffling one of them and then stacking 
the others to match ... or by some more symmetric process. 
In any case the result is symmetric w.r.t interchange of 
decks.  In this situation, I can choose any one of the 
decks and obtain 225 bits of entropy.  The funny thing 
is that if I choose N of the decks, I still get only 225 
bits of entropy, not N*225.

This can be summarized by saying that entropy is not an
extensive quantity in this situation.  The graph of
entropy versus N goes like this:

     225        *   *   *   *   *

       0    *
            0   1   2   3   4   5  (# of decks)

The spooky aspect of this situation is the whack-a-mole 
aspect:  You cannot decide in advance which one of the 
decks has entropy and which N-1 of them do not.  That's 
the wrong question.  The first deck we choose to look 
at has 225 bits of entropy, and only then can we say 
that the other N-1 decks have zero additional entropy.

The original question spoke of "trusted" sources of
entropy, and I answered accordingly.  To the extent
that the sources are correlated, they were never eligible 
to be considered trusted sources of entropy.  To say 
the same thing the other way around, to the extent
that each source can be trusted to provide a certain
amount of entropy, it must be to that extent independent 
of the others.

It is possible for a source to be partially dependent
and partially independent.  For example, if you take
each of the ten aforementioned decks and "cut the deck"
randomly and independently, that means the first deck
we look at will provide 225 bits of entropy, and each
one thereafter will provide 5.7 bits of additional
entropy, since log2(52)=5.7.  So in this situation,
each deck can be /trusted/ to provide 5.7 bits of
entropy.

In this situation, requiring each deck to have "no
input" from the other decks would be an overly strict
requirement.  We do not need full independence;  we
just need some independence, as quantified by the
provable lower bound on the entropy.

If you wanted, you could do a deeper analysis of this 
example, taking into account the fact that 5.7 is not 
the whole story.  It is easy to use 5.7 bits as a valid 
and trustworthy lower bound, but under some conditions 
more entropy is available, and can be quantified by
considering the _joint_ probability distribution and
computing the entropy of that distribution.  Meanwhile
the fact remains that under a wide range of practical 
conditions, it makes sense to engineer a randomness 
generator based on provable lower bounds, since that 
is good enough to get the job done, and a deeper
analysis would not be worth the trouble.
  http://www.av8n.com/turbid/paper/turbid.htm


> If the issue is how to make sure you get out at least all the randomness
> that was there,

I'm going to ignore the "At least".  It is very hard to 
get out more than you put in.

On a less trivial note:  The original question did not
require getting out every last bit of available randomness.
In situations where the sources might be partially
independent and partially dependent, that would be a 
very hard challenge, and I do not wish to accept that 
challenge.

Dealing with provable lower bounds on the entropy is
more tractable, and sufficient for a wide range of
practical purposes.

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