Ensuring Even Distribution of Hash Values
Because of the potential for collisions (duplicate hash values for different documents), designers of hashing functions take extra care to ensure an even distribution of hash values. That is, they want to make sure that if there are 16 possible hash value results that approximately as many documents hash to a value of 9 as to 13. If 99% of documents hash to 15 using a particular hashing algorithm, that algorithm doesnt have an even distribution and is thus weaker than those that do. Because of the requirement for an even distribution of hash values, good hashing algorithms tend to be computationally complex, taking a relatively significant amount of CPU time to perform. The evenness of distribution doesnt have to be perfect, but the more well distributed potential hash values are, the more difficult it is to attack the problem of finding a plausible duplicate document.
It is impossible to ascertain the contents of a program or message from the hash value alone. That is, the hashing algorithm is one way. You can put a document through a hashing algorithm and get back a hash value as a result. However, you cannot put a hash value through a hashing algorithm and get back the original document as a result. Why is this? For the same reason that a bitmap compressed into a JPEG file cant be turned back into the original bitmap with complete accuracy the hash is only a summary of the original document, and some information is lost during the summarization process.
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