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The MD5 message-digest algorithm is a widely used hash function producing a 128-bit hash value. MD5 was designed by Ronald Rivest in 1991 to replace an earlier hash function MD4, [3] and was specified in 1992 as RFC 1321. MD5 can be used as a checksum to verify data integrity against unintentional corruption.
hash GOST: 256 bits hash Grøstl: up to 512 bits 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 ...
In cryptography, the Merkle–Damgård construction or Merkle–Damgård hash function is a method of building collision-resistant cryptographic hash functions from collision-resistant one-way compression functions. [1]: 145 This construction was used in the design of many popular hash algorithms such as MD5, SHA-1, and SHA-2.
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.
In the example given above the result is formed as follows, where MD5() represents a function used to calculate an MD5 hash, backslashes represent a continuation and the quotes shown are not used in the calculation. Completing the example given in RFC 2617 gives the following results for each step.
MD5 was designed by Ronald Rivest in 1991 to replace an earlier hash function, MD4, and was specified in 1992 as RFC 1321. Collisions against MD5 can be calculated within seconds, which makes the algorithm unsuitable for most use cases where a cryptographic hash is required. MD5 produces a digest of 128 bits (16 bytes).
Rainbow tables are a practical example of a space–time tradeoff: they use less computer processing time and more storage than a brute-force attack which calculates a hash on every attempt, but more processing time and less storage than a simple table that stores the hash of every possible password.
Truncating the resulting hash to achieve K-anonymity; The degree to which a resulting hash is truncated is a balancing act between the privacy offered and the desired collision rate (the probability that one anonymised MAC Address will overlap with another).