ok

On 23/01/14 23:38, "Krisztián Pintér" <[email protected]> wrote:

>
>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.
>
>you can only do better if you have an idea about the process that
>created the data. for example you might assume that it is mostly
>thermal noise. you can assume that thermal noise has some frequency
>distribution, or energy or whatever, etc. within this assumption, you
>can determine the entropy content by measurements. but at this point,
>you are pretty much prone to two errors: 1, what if your assumption is
>wrong and 2, what if your physical model overestimates the
>unpredictability of the given system. example for the former: the
>signal might be largely controllable by an external EM interference,
>and then you measure not noise, but attacker controlled data. example
>for the latter: a smartass scientist might come up with a better
>physical model for thermal noise.
>
>it is also important to note that entropy is observer dependent. we
>actually talk about the entropy as seen by the attacker. but it is not
>straightforward to assess what is actually visible to an attacker and
>what is not. observation methods improve with time.
>
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