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Nice. I have a machine-learning application, doing statistical NLP over a large corpus. After a few initial passes of morphological normalization on the original words in the text, I throw away the string values and use hash codes instead. Throughout my entire corpus, there are about 600,000 unique words, and using the default java hashcode function, I was getting about 3.5% collisions. But if I SHA-256 the string value and then generate a hashcode from the digested string, the collision ratio is less than 0.0001%. Thanks!

benjismith
– benjismith

2010-11-18 18:54:30 +00:00
Commented Nov 18, 2010 at 18:54
29

@benjismith One in a million is far too large... is "less than 0.0001%" an oblique way of saying "exactly 0"? I really doubt that you saw a SHA-256 collision because that has never been observed, anywhere, ever; not even for 160-bit SHA-1. If you have two strings that produce the same SHA-256, the security community would love to see them; you'll be world-famous... in a very obscure way. See Comparison of SHA Functions

Tim Sylvester
– Tim Sylvester

2014-02-26 01:03:22 +00:00
Commented Feb 26, 2014 at 1:03
10

@TimSylvester, you misunderstood. I didn't find SHA-256 collisions. I computed the SHA-256 and then fed the resultant byte sequences into a typical Java "hashCode" function, because I needed a 32-bit hash. That's where I found the collisions. Nothing remarkable :)

benjismith
– benjismith

2014-02-27 05:09:23 +00:00
Commented Feb 27, 2014 at 5:09
1

Isn't there a difference between 'hashing' and 'encrypting'? I understand MessageDigest is a one way hashing function, right? Also, when I used the function, I got the hashed string as a lot of junk UTF characters when I opened the file in LibreOffice. Is it possible to get the hashed string as a random bunch of alphanumeric characters instead of junk UTF characters?

Nav
– Nav

2016-11-13 17:54:54 +00:00
Commented Nov 13, 2016 at 17:54
2

String encryptedString and stringToEncrypt.getBytes() refer to encryption, when this really is a hashing algorithm.

Shawn
– Shawn

2017-05-10 17:43:52 +00:00
Commented May 10, 2017 at 17:43

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