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Cryptographic Hash Function
A cryptographic hash function is a special class of hash function that has certain properties which make it suitable for use in cryptography. It is a mathematical algorithm that maps data of arbitrary size to a bit string of a fixed size (a hash) and is designed to be a one-way function, that is, a function which is infeasible to invert. The only way to recreate the input data from an ideal cryptographic hash function's output is to attempt a brute-force search of possible inputs to see if they produce a match, or use a rainbow table of matched hashes
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Concatenation
In formal language theory and computer programming, string concatenation is the operation of joining character strings end-to-end. For example, the concatenation of "snow" and "ball" is "snowball". In some but not all formalisations of concatenation theory, also called string theory, string concatenation is a primitive notion.Contents1 Syntax 2 Implementation 3 Concatenation of sets of strings 4 Algebraic properties 5 Applications5.1 Audio/telephony 5.2 Database theory6 See also 7 ReferencesSyntax[edit] In many programming languages, string concatenation is a binary infix operator. The + (plus) operator is often overloaded to denote concatenation for string arguments: "Hello, " + "World" has the value "Hello, World". In other languages there is a separate operator, particularly to specify implicit type conversion to string, as opposed to more complicated behavior for generic plus. Examples include . in Edinburgh IMP, Perl, and PHP, .
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Adversary (cryptography)
In cryptography, an adversary (rarely opponent, enemy) is a malicious entity whose aim is to prevent the users of the cryptosystem from achieving their goal (primarily privacy, integrity, and availability of data). An adversary's efforts might take the form of attempting to discover secret data, corrupting some of the data in the system, spoofing the identity of a message sender or receiver, or forcing system downtime. Actual adversaries, as opposed to idealized ones, are referred to as attackers. Not surprisingly, the former term predominates in the cryptographic and the latter in the computer security literature. Eve, Mallory, Oscar and Trudy are all adversarial characters widely used in both types of texts. This notion of an adversary helps both intuitive and formal reasoning about cryptosystems by casting security analysis of cryptosystems as a 'game' between the users and a centrally co-ordinated enemy
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String (computer Science)
In computer programming, a string is traditionally a sequence of characters, either as a literal constant or as some kind of variable. The latter may allow its elements to be mutated and the length changed, or it may be fixed (after creation). A string is generally understood as a data type and is often implemented as an array data structure of bytes (or words) that stores a sequence of elements, typically characters, using some character encoding
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Random Function
In probability theory and related fields, a stochastic or random process is a mathematical object usually defined as a collection of random variables. Historically, the random variables were associated with or indexed by a set of numbers, usually viewed as points in time, giving the interpretation of a stochastic process representing numerical values of some system randomly changing over time, such as the growth of a bacterial population, an electrical current fluctuating due to thermal noise, or the movement of a gas molecule.[1][4][5] Stochastic processes are widely used as mathematical models of systems and phenomena that appear to vary in a random manner
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Authentication
Authentication
Authentication
(from Greek: αὐθεντικός authentikos, "real, genuine", from αὐθέντης authentes, "author") is the act of confirming the truth of an attribute of a single piece of data claimed true by an entity. In contrast with identification, which refers to the act of stating or otherwise indicating a claim purportedly attesting to a person or thing's identity, authentication is the process of actually confirming that identity. It might involve confirming the identity of a person by validating their identity documents, verifying the authenticity of a website with a digital certificate,[1] determining the age of an artifact by carbon dating, or ensuring that a product is what its packaging and labeling claim to be
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CRC32
A cyclic redundancy check (CRC) is an error-detecting code commonly used in digital networks and storage devices to detect accidental changes to raw data. Blocks of data entering these systems get a short check value attached, based on the remainder of a polynomial division of their contents. On retrieval, the calculation is repeated and, in the event the check values do not match, corrective action can be taken against data corruption. CRCs can be used for error correction (see bitfilters).[1] CRCs are so called because the check (data verification) value is a redundancy (it expands the message without adding information) and the algorithm is based on cyclic codes. CRCs are popular because they are simple to implement in binary hardware, easy to analyze mathematically, and particularly good at detecting common errors caused by noise in transmission channels
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Cyclic Redundancy Check
A cyclic redundancy check (CRC) is an error-detecting code commonly used in digital networks and storage devices to detect accidental changes to raw data. Blocks of data entering these systems get a short check value attached, based on the remainder of a polynomial division of their contents. On retrieval, the calculation is repeated and, in the event the check values do not match, corrective action can be taken against data corruption. CRCs can be used for error correction (see bitfilters).[1] CRCs are so called because the check (data verification) value is a redundancy (it expands the message without adding information) and the algorithm is based on cyclic codes. CRCs are popular because they are simple to implement in binary hardware, easy to analyze mathematically, and particularly good at detecting common errors caused by noise in transmission channels
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Information Security
Information
Information
security, sometimes shortened to InfoSec, is the practice of preventing unauthorized access, use, disclosure, disruption, modification, inspection, recording or destruction of information
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Deterministic Algorithm
In computer science, a deterministic algorithm is an algorithm which, given a particula, will always produce the same output, with the underlying machine always passing through the same sequence of states. Deterministic algorithms are by far the most studied and familiar kind of algorithm, as well as one of the most practical, since they can be run on real machines efficiently. Formally, a deterministic algorithm computes a mathematical function; a function has a unique value for any input in its domain, and the algorithm is a process that produces this particular value as output.Contents1 Formal definition 2 What makes algorithms non-deterministic? 3 Disadvantages of Determinism 4 Determinism categories in languages4.1 Mercury 4.2 Haskell 4.3 ML family and derived languages 4.4 Java5 ReferencesFormal definition[edit] Deterministic algorithms can be defined in terms of a state machine: a state describes what a machine is doing at a particular instant in time
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Bruce Schneier
Bruce Schneier
Bruce Schneier
(/ˈʃnaɪ.ər/; born December 15, 1952[1]) is an American cryptographer, computer security professional, privacy specialist and writer. He is the author of several books on general security topics, computer security and cryptography. Schneier is a fellow at the Berkman Center for Internet & Society at Harvard Law School, a program fellow at the New America Foundation's Open Technology Institute
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Wired Equivalent Privacy
Wired Equivalent Privacy (WEP) is a security algorithm for IEEE 802.11 wireless networks. Introduced as part of the original 802.11 standard ratified in 1997, its intention was to provide data confidentiality comparable to that of a traditional wired network.[1] WEP, recognizable by its key of 10 or 26 hexadecimal digits (40 or 104 bits), was at one time widely in use and was often the first security choice presented to users by router configuration tools.[2][3] In 2003 the Wi-Fi Alliance
Wi-Fi Alliance
announced that WEP had been superseded by Wi-Fi Protected Access
Wi-Fi Protected Access
(WPA). In 2004, with the ratification of the full 802.11i standard (i.e. WPA2), the IEEE declared that both WEP-40 and WEP-104 have been deprecated.[4] WEP was the only encryption protocol available to 802.11a and 802.11b devices built before the WPA standard, which was available for 802.11g devices
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Brute-force Search
In computer science, brute-force search or exhaustive search, also known as generate and test, is a very general problem-solving technique that consists of systematically enumerating all possible candidates for the solution and checking whether each candidate satisfies the problem's statement. A brute-force algorithm to find the divisors of a natural number n would enumerate all integers from 1 to n, and check whether each of them divides n without remainder. A brute-force approach for the eight queens puzzle would examine all possible arrangements of 8 pieces on the 64-square chessboard, and, for each arrangement, check whether each (queen) piece can attack any other. While a brute-force search is simple to implement, and will always find a solution if it exists, its cost is proportional to the number of candidate solutions – which in many practical problems tends to grow very quickly as the size of the problem increases
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Computational Complexity Theory
Computational complexity theory is a branch of the theory of computation in theoretical computer science that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other. A computational problem is understood to be a task that is in principle amenable to being solved by a computer, which is equivalent to stating that the problem may be solved by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used. The theory formalizes this intuition, by introducing mathematical models of computation to study these problems and quantifying the amount of resources needed to solve them, such as time and storage
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Bit String
A bit array (also known as bit map , bit set, bit string, or bit vector) is an array data structure that compactly stores bits. It can be used to implement a simple set data structure. A bit array is effective at exploiting bit-level parallelism in hardware to perform operations quickly. A typical bit array stores kw bits, where w is the number of bits in the unit of storage, such as a byte or word, and k is some nonnegative integer. If w does not divide the number of bits to be stored, some space is wasted due to internal fragmentation.Contents1 Definition 2 Basic operations 3 More complex operations3.1 Population / Hamming weight 3.2 Inversion 3.3 Find first one4 Compression 5 Advantages and disadvantages 6 Applications 7 Language support 8 See also 9 References 10 External linksDefinition[edit] A bit array is a mapping from some domain (almost always a range of integers) to values in the set 0, 1
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Map (mathematics)
In mathematics, the term mapping, sometimes shortened to map, refers to either a function, often with some sort of special structure, or a morphism in category theory, which generalizes the idea of a function. There are also a few, less common uses in logic and graph theory.Contents1 Maps as functions 2 Maps as morphisms 3 Other uses3.1 In logic 3.2 In graph theory 3.3 In computer science4 See also 5 ReferencesMaps as functions[edit] Main article: Function (mathematics) In many branches of mathematics, the term map is used to mean a function, sometimes with a specific property of particular importance to that branch. For instance, a "map" is a continuous function in topology, a linear transformation in linear algebra, etc. Some authors, such as Serge Lang,[1] use "function" only to refer to maps in which the codomain is a set of numbers (i.e
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