From: J.A. Terranson <measl@mfn.org> Interesting thread going on at dsfjdssdfsd@ietf.org. Forwarded for our collective interest and amusement. ---------- Forwarded message ---------- Date: Thu, 23 Jan 2014 23:38:07 +0100 From: Krisztián Pintér <pinterkr@gmail.com> To: Michael Hammer <michael.hammer@yaanatech.com> Cc: "dsfjdssdfsd@ietf.org" <dsfjdssdfsd@ietf.org>, "ietf@hosed.org" <ietf@hosed.org> Subject: Re: [dsfjdssdfsd] Any plans for drafts or discussions on here? Michael Hammer (at Thursday, January 23, 2014, 9:49:32 PM):
This may get off-topic, but are there good software tools for testing entropy, that could help applications determine if the underlying system is giving them good input?
disclaimer: i'm no expert, it is just what i gathered. (i'm pretty much interested in randomness.) short answer: no long answer: in some situations yes. if you are handed a bunch of data, all you can do is to try different techniques to put an upper limit on the entropy. for example you can calculate the shannon entropy assuming independent bits. then you can hypothesize some interdependence, and see if you can compress the data. you can apply different lossless compression methods. the better compression you find puts an upper limit on the entropy. but never a lower limit.
Consider this: Suppose I handed you the digits of pi, the digits from the millionth digit to the two-millionth digit, and I asked you to determine if they are 'random'. By many tests, you'd conclude that they are random. (Or, at least 'normal' http://en.wikipedia.org/wiki/Normal_numbers ) But, in reality they are highly non-random, precisely because they are a million sequential digits of pi. But you wouldn't know that, if you didn't know that. Jim Bell