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I transcend this problem by making all my database passwords 'abcd'
Reminds me of https://xkcd.com/936/ I think "correct horse battery staple" has a low entropy, since it is just ordinary looking words (strings).
I transcend this problem by making all my database passwords 'abcd'
The tool found "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz1234567890" in our codebase as a high entropy line :)
The approach is simple: Turn the file into a stream of tokens. For each token, ask a language model to generate the full set of predictions based on context, and sort based on likelihood. Look where the actual token appears in the sorted list. Low entropy symbols will be near the start of the list, and high entropy tokens near the end.
I suspect most language models would deal with your alphabet example just fine, while still correctly spotting passwords and API keys. It would be a fun experiment to try!
Is there any good posts about the use of entropy for tasks like that? I am wondering for quite some time of how do people actually use it and if it is any effective, but never actually got to investigating the problem myself. First of all, how to define "entropy" for text is a bit unclear in the first place. Here it's as simple as `-Sum(x log(x))` where x = countOccurences(char) / len(text). And that raises a lot of…
Entropy of a particular string isn't a rigorous mathematical idea, since by definition the string which is known can only take one value, the "entropy" is therefore zero bits. The reason why we can distinguish non-random data from random is that only a small subset of all possible states are considered useful for humans, and since we have an idea what that subset looks like, we can try to estimate what process was us…
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Not sure; you can use the same character instead of a space and still get a few bits. Of course different ones would be better, but again, depends on how many bits you actually need.
I thought the point was to construct a password that's secure enough _and_ easy to remember for humans. Adding random punctuation helps with the former, but might interfere with the latter. (In the extreme case, you just generate completely random strings character for character. That's the most secure, but the least memorable.)
key word here, I think we agree ;)
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Entropy is a measure of complexity or disorder of a signal. The interesting part is that the disorder is with respect to the proper basis or dictionary. Something can look complex in one encoding but be low entropy in the right encoding. You need to know the right basis, or figure it out from the context, to accurately determine the entropy of a signal. A much stronger way of building a tool like the OP is to have a…
bookmarking to think about later... does this hold for representing numbers as one base compared to another? Regarding a prime as having higher entropy / less structure than say a perfect square or highly divisible number a prime is a prime in any base, but the number of divisors will differ in non-primes, if the number is divisible by the base then it may appear to have more structure (smaller function necessary to…
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Not really, advertising is really the only field of human endeavour that is both data-driven and results-oriented. (Doesn't still stop smart people from committing fraud, but that is a different story.)
Unfortunately I beg to differ. I worked for several companies where we the management clearly saw that the results were very poor (for Facebook ads, for example) but continued to invest because there is a defined budget for it and so on. It was like this last year and 20 years ago.
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bookmarking to think about later... does this hold for representing numbers as one base compared to another? Regarding a prime as having higher entropy / less structure than say a perfect square or highly divisible number a prime is a prime in any base, but the number of divisors will differ in non-primes, if the number is divisible by the base then it may appear to have more structure (smaller function necessary to…
Also bookmarking to think about it. My mind drifted towards Fourier transform. Using the transform as a way of describing a system with less entropy? Or am I butchering all of mathematics by making this comparison?
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Entropy of a particular string isn't a rigorous mathematical idea, since by definition the string which is known can only take one value, the "entropy" is therefore zero bits. The reason why we can distinguish non-random data from random is that only a small subset of all possible states are considered useful for humans, and since we have an idea what that subset looks like, we can try to estimate what process was us…
If you’re looking for a rigorous mathematical idea, what people are trying to measure is the Kolmogorov complexity of the code. Measuring the compressed length is a rough estimate of that value. https://en.m.wikipedia.org/wiki/Kolmogorov_complexity
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Entropy is a measure of complexity or disorder of a signal. The interesting part is that the disorder is with respect to the proper basis or dictionary. Something can look complex in one encoding but be low entropy in the right encoding. You need to know the right basis, or figure it out from the context, to accurately determine the entropy of a signal. A much stronger way of building a tool like the OP is to have a…
bookmarking to think about later... does this hold for representing numbers as one base compared to another? Regarding a prime as having higher entropy / less structure than say a perfect square or highly divisible number a prime is a prime in any base, but the number of divisors will differ in non-primes, if the number is divisible by the base then it may appear to have more structure (smaller function necessary to…
Could you please present an example of this?
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bookmarking to think about later... does this hold for representing numbers as one base compared to another? Regarding a prime as having higher entropy / less structure than say a perfect square or highly divisible number a prime is a prime in any base, but the number of divisors will differ in non-primes, if the number is divisible by the base then it may appear to have more structure (smaller function necessary to…
Changing the base of number representation with a random basis feels like XORing a string with a random string, which is to say you're adding entropy equal to the random string. My thinking is that for any number representation M, you can get any other number representation N given a well-chosen base. So when presented with the encoded N, the original number could be any other number with the same number of digits. B…
Not necessarily the same number of digits, when changing the base the number of digits may change as well. E.g., decimal 8 becomes 1000 in binary.