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Hash Collision
In computer science, a hash collision or hash clash is when two distinct pieces of data in a hash table share the same hash value. The hash value in this case is derived from a hash function which takes a data input and returns a fixed length of bits. Although hash algorithms, especially cryptographic hash algorithms, have been created with the intent of being Collision resistance, collision resistant, they can still sometimes map different data to the same hash (by virtue of the pigeonhole principle). Malicious users can take advantage of this to mimic, access, or alter data. Due to the possible negative applications of hash collisions in data management and computer security (in particular, cryptographic hash functions), collision avoidance has become an important topic in computer security. Background Hash collisions can be unavoidable depending on the number of objects in a set and whether or not the bit string they are mapped to is long enough in length. When there is a s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hash Table 4 1 1 0 0 1 0 LL
Hash, hashes, hash mark, or hashing may refer to: Substances * Hash (food), a coarse mixture of ingredients, often based on minced meat * Hash (stew), a pork and onion-based gravy found in South Carolina * Hash, a nickname for hashish, a cannabis product Hash mark * Hash mark (sports), a marking on hockey rinks and gridiron football fields * Hatch marks, hash marks or tick marks, a form of mathematical notation * Number sign (#), also known as the hash, hash mark, or (in American English) pound sign * Service stripe, a military and paramilitary decoration * Tally mark, a counting notation * Checkmate symbol in chess Computing * Hash function, an encoding of data into a small, fixed size; used in hash tables and cryptography ** Hash table, a data structure using hash functions ** Cryptographic hash function, a hash function used to authenticate message integrity * URI fragment, in computer hypertext, a string of characters that refers to a subordinate resource * Geohash, a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Locality-sensitive Hashing
In computer science, locality-sensitive hashing (LSH) is a fuzzy hashing technique that hashes similar input items into the same "buckets" with high probability. (The number of buckets is much smaller than the universe of possible input items.) Since similar items end up in the same buckets, this technique can be used for data clustering and nearest neighbor search. It differs from conventional hashing techniques in that hash collisions are maximized, not minimized. Alternatively, the technique can be seen as a way to reduce the dimensionality of high-dimensional data; high-dimensional input items can be reduced to low-dimensional versions while preserving relative distances between items. Hashing-based approximate nearest-neighbor search algorithms generally use one of two main categories of hashing methods: either data-independent methods, such as locality-sensitive hashing (LSH); or data-dependent methods, such as locality-preserving hashing (LPH). Locality-preserving hashin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cache (computing)
In computing, a cache ( ) is a hardware or software component that stores data so that future requests for that data can be served faster; the data stored in a cache might be the result of an earlier computation or a copy of data stored elsewhere. A cache hit occurs when the requested data can be found in a cache, while a cache miss occurs when it cannot. Cache hits are served by reading data from the cache, which is faster than recomputing a result or reading from a slower data store; thus, the more requests that can be served from the cache, the faster the system performs. To be cost-effective, caches must be relatively small. Nevertheless, caches are effective in many areas of computing because typical Application software, computer applications access data with a high degree of locality of reference. Such access patterns exhibit temporal locality, where data is requested that has been recently requested, and spatial locality, where data is requested that is stored near dat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Quadratic Probing
Quadratic probing is an open addressing scheme in computer programming for resolving hash collisions in hash tables. Quadratic probing operates by taking the original hash index and adding successive values of an arbitrary quadratic polynomial until an open slot is found. An example sequence using quadratic probing is: H + 1^2 , H + 2^2 , H + 3^2 , H + 4^2 , ... , H + k^2 Quadratic probing is often recommended as an alternative to linear probing because it incurs less clustering. Quadratic probing exhibits better locality of reference than many other hash table such as chaining; however, for queries, quadratic probing does not have as good locality as linear probing, causing the latter to be faster in some settings. Quadratic probing was first introduced by Ward Douglas Maurer in 1968. Quadratic function Let ''h''(''k'') be a hash function that maps an element ''k'' to an integer in , ''m''−1 where ''m'' is the size of the table. Let the ''i''th probe position for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Double Hashing
Double hashing is a computer programming technique used in conjunction with open addressing in hash tables to resolve hash collisions, by using a secondary hash of the key as an offset when a collision occurs. Double hashing with open addressing is a classical data structure on a table T. The double hashing technique uses one hash value as an index into the table and then repeatedly steps forward an interval until the desired value is located, an empty location is reached, or the entire table has been searched; but this interval is set by a second, independent hash function. Unlike the alternative collision-resolution methods of linear probing and quadratic probing, the interval depends on the data, so that values mapping to the same location have different bucket sequences; this minimizes repeated collisions and the effects of clustering. Given two random, uniform, and independent hash functions h_1 and h_2, the ith location in the bucket sequence for value k in a hash table of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linear Probing
Linear probing is a scheme in computer programming for resolving hash collision, collisions in hash tables, data structures for maintaining a collection of Attribute–value pair, key–value pairs and looking up the value associated with a given key. It was invented in 1954 by Gene Amdahl, Elaine M. McGraw, and Arthur Samuel (computer scientist), Arthur Samuel and first analyzed in 1963 by Donald Knuth. Along with quadratic probing and double hashing, linear probing is a form of open addressing. In these schemes, each cell of a hash table stores a single key–value pair. When the hash function causes a collision by mapping a new key to a cell of the hash table that is already occupied by another key, linear probing searches the table for the closest following free location and inserts the new key there. Lookups are performed in the same way, by searching the table sequentially starting at the position given by the hash function, until finding a cell with a matching key or an e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Separate Chaining
In computer science, a hash table is a data structure that implements an associative array, also called a dictionary or simply map; an associative array is an abstract data type that maps keys to values. A hash table uses a hash function to compute an ''index'', also called a ''hash code'', into an array of ''buckets'' or ''slots'', from which the desired value can be found. During lookup, the key is hashed and the resulting hash indicates where the corresponding value is stored. A map implemented by a hash table is called a hash map. Most hash table designs employ an imperfect hash function. Hash collisions, where the hash function generates the same index for more than one key, therefore typically must be accommodated in some way. In a well-dimensioned hash table, the average time complexity for each lookup is independent of the number of elements stored in the table. Many hash table designs also allow arbitrary insertions and deletions of key–value pairs, at amortiz ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Open Addressing
Open addressing, or closed hashing, is a method of Hash table#Collision resolution, collision resolution in hash tables. With this method a hash collision is resolved by probing, or searching through alternative locations in the array (the ''probe sequence'') until either the target record is found, or an unused array slot is found, which indicates that there is no such key in the table. Well-known probe sequences include: ; Linear probing : in which the interval between probes is fixed — often set to 1. ; Quadratic probing : in which the interval between probes increases linearly (hence, the indices are described by a quadratic function). ; Double hashing : in which the interval between probes is fixed for each record but is computed by another hash function. The main trade offs between these methods are that linear probing has the best Locality of reference, cache performance but is most sensitive to Primary clustering, clustering, while double hashing has poor cache perf ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Collision Attack
In cryptography, a collision attack on a cryptographic hash tries to find two inputs producing the same hash value, i.e. a hash collision. This is in contrast to a preimage attack where a specific target hash value is specified. There are roughly two types of collision attacks: ;Classical collision attack: Find two different messages ''m''1 and ''m''2 such that ''hash''(''m''1) = ''hash''(''m''2). More generally: ;Chosen-prefix collision attack: Given two different prefixes ''p''1 and ''p''2, find two suffixes ''s''1 and ''s''2 such that ''hash''(''p''1 ∥ ''s''1) = ''hash''(''p''2 ∥ ''s''2), where ∥ denotes the concatenation operation. Classical collision attack Much like symmetric-key ciphers are vulnerable to brute force attacks, every cryptographic hash function is inherently vulnerable to collisions using a birthday attack. Due to the birthday problem, these attacks are much faster than a brute force would be. A hash of ''n'' bits can be broken in 2''n''/2 time steps (e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Checksum
A checksum is a small-sized block of data derived from another block of digital data for the purpose of detecting errors that may have been introduced during its transmission or storage. By themselves, checksums are often used to verify data integrity but are not relied upon to verify data authenticity. The procedure which generates this checksum is called a checksum function or checksum algorithm. Depending on its design goals, a good checksum algorithm usually outputs a significantly different value, even for small changes made to the input. 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. Checksum functions are related to hash functions, fingerprints, randomization functio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Homology (biology)
In biology, homology is similarity in anatomical structures or genes between organisms of different taxa due to shared ancestry, ''regardless'' of current functional differences. Evolutionary biology explains homologous structures as retained heredity from a common descent, common ancestor after having been subjected to adaptation (biology), adaptive modifications for different purposes as the result of natural selection. The term was first applied to biology in a non-evolutionary context by the anatomist Richard Owen in 1843. Homology was later explained by Charles Darwin's theory of evolution in 1859, but had been observed before this from Aristotle's biology onwards, and it was explicitly analysed by Pierre Belon in 1555. A common example of homologous structures is the forelimbs of vertebrates, where the bat wing development, wings of bats and origin of avian flight, birds, the arms of primates, the front flipper (anatomy), flippers of whales, and the forelegs of quadrupedalis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
