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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 ...
Perceptual hashing is the use of a fingerprinting algorithm that produces a snippet, hash, or fingerprint of various forms of multimedia. [ 1 ] [ 2 ] A perceptual hash is a type of locality-sensitive hash , which is analogous if features of the multimedia are similar.
In computer science, locality-sensitive hashing (LSH) is a fuzzy hashing technique that hashes similar input items into the same "buckets" with high probability. [1] ( The number of buckets is much smaller than the universe of possible input items.) [1] Since similar items end up in the same buckets, this technique can be used for data clustering and nearest neighbor search.
740 × 536 (15 KB) Lichtspiel: Try to fix ordering of letters: 07:24, 12 June 2011: 740 × 536 (15 KB) Lichtspiel: Use 'Courier' font again, use different approach to highlight changes: 07:13, 12 June 2011: 740 × 536 (15 KB) Lichtspiel: Resize, use red colour for changes, use font 'Courier 10 Pitch' 04:57, 27 November 2008: 806 × 600 (13 KB ...
The following tables compare general and technical information for a number of cryptographic hash functions. See the individual functions' articles for further information. This article is not all-inclusive or necessarily up-to-date. An overview of hash function security/cryptanalysis can be found at hash function security summary.
BLAKE is a cryptographic hash function based on Daniel J. Bernstein's ChaCha stream cipher, but a permuted copy of the input block, XORed with round constants, is added before each ChaCha round. Like SHA-2 , there are two variants differing in the word size.
520 × 352 (97 KB) Citypeek: Valid SVG now. 01:42, 2 December 2005: 520 × 352 (18 KB) Helix84 == Summary == A typical hash function at work. Note that the hash sums always are the same size, no matter how short or long the input is and also note that the hash sums look very different even when there are only slight differences in the input.