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A file can become corrupted by a variety of ways: faulty storage media, errors in transmission, write errors during copying or moving, software bugs, and so on. Hash-based verification ensures that a file has not been corrupted by comparing the file's hash value to a previously calculated value. If these values match, the file is presumed to be ...
The MD5 hash functions as a compact digital fingerprint of a file. As with all such hashing algorithms, there is theoretically an unlimited number of files that will have any given MD5 hash. However, it is very unlikely that any two non-identical files in the real world will have the same MD5 hash, unless they have been specifically created to ...
For example, if the input is 123 456 789 and the hash table size 10 000, then squaring the key produces 15 241 578 750 190 521, so the hash code is taken as the middle 4 digits of the 17-digit number (ignoring the high digit) 8750. The mid-squares method produces a reasonable hash code if there is not a lot of leading or trailing zeros in the key.
The lookup3 function consumes input in 12 byte (96 bit) chunks. [9] It may be appropriate when speed is more important than simplicity. Note, though, that any speed improvement from the use of this hash is only likely to be useful for large keys, and that the increased complexity may also have speed consequences such as preventing an optimizing compiler from inlining the hash function.
hash HAS-160: 160 bits hash HAVAL: 128 to 256 bits hash JH: 224 to 512 bits hash LSH [19] 256 to 512 bits wide-pipe Merkle–Damgård construction: MD2: 128 bits hash MD4: 128 bits hash MD5: 128 bits Merkle–Damgård construction: MD6: up to 512 bits Merkle tree NLFSR (it is also a keyed hash function) RadioGatún: arbitrary ideal mangling ...
This is especially true of cryptographic hash functions, which may be used to detect many data corruption errors and verify overall data integrity; if the computed checksum for the current data input matches the stored value of a previously computed checksum, there is a very high probability the data has not been accidentally altered or corrupted.
MurmurHash is a non-cryptographic hash function suitable for general hash-based lookup. [1] [2] [3] It was created by Austin Appleby in 2008 [4] and, as of 8 January 2016, [5] is hosted on GitHub along with its test suite named SMHasher. It also exists in a number of variants, [6] all of which have been released into the public domain. The name ...
For example, in an ed2k link, an MD4-variant hash is combined with the file size, providing sufficient information for locating file sources, downloading the file, and verifying its contents. Magnet links are another example. Such file hashes are often the top hash of a hash list or a hash tree, which allows for additional benefits.