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A hash function that allows only certain table sizes or strings only up to a certain length, or cannot accept a seed (i.e. allow double hashing) is less useful than one that does. [citation needed] A hash function is applicable in a variety of situations. Particularly within cryptography, notable applications include: [8]
Fowler–Noll–Vo hash function (FNV Hash) 32, 64, 128, 256, 512, or 1024 bits xor/product or product/XOR Jenkins hash function: 32 or 64 bits XOR/addition Bernstein's hash djb2 [2] 32 or 64 bits shift/add or mult/add or shift/add/xor or mult/xor PJW hash / Elf Hash: 32 or 64 bits add,shift,xor MurmurHash: 32, 64, or 128 bits product/rotation ...
Non-cryptographic hash functions optimized for software frequently involve the multiplication operation. Since in-hardware multiplication is resource-intensive and frequency-limiting, ASIC-friendlier designs had been proposed, including SipHash (which has an additional benefit of being able to use a secret key for message authentication), NSGAhash, and XORhash.
Here is the formal technical definition of the puzzle friendliness property. [2] [1]A hash function H is said to be puzzle friendly if for every possible n-bit output value y, if k is chosen with a distribution with high min-entropy, then it is infeasible to find x such that H( k || x) = y (where the symbol "||" denotes concatenation) in time significantly less than 2 n.
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.
A snippet of Python code with keywords highlighted in bold yellow font. The syntax of the Python programming language is the set of rules that defines how a Python program will be written and interpreted (by both the runtime system and by human readers). The Python language has many similarities to Perl, C, and Java. However, there are some ...
Mask generation functions, as generalizations of hash functions, are useful wherever hash functions are. However, use of a MGF is desirable in cases where a fixed-size hash would be inadequate. Examples include generating padding, producing one-time pads or keystreams in symmetric-key encryption, and yielding outputs for pseudorandom number ...
Hash-based signature schemes use one-time signature schemes as their building block. A given one-time signing key can only be used to sign a single message securely. Indeed, signatures reveal part of the signing key. The security of (hash-based) one-time signature schemes relies exclusively on the security of an underlying hash function.