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TRNG
In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), or physical random number generator is a device that generates random numbers from a physical process capable of producing entropy, unlike a pseudorandom number generator (PRNG) that utilizes a deterministic algorithm and non-physical nondeterministic random bit generators that do not include hardware dedicated to generation of entropy. Many natural phenomena generate low-level, statistically random "noise" signals, including thermal and shot noise, jitter and metastability of electronic circuits, Brownian motion, and atmospheric noise. Researchers also used the photoelectric effect, involving a beam splitter, other quantum phenomena, and even the nuclear decay (due to practical considerations the latter, as well as the atmospheric noise, is not viable except for fairly restricted applications or online distribution services). While "cl ...
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Non-physical Nondeterministic Random Bit Generator
Non-physical true random number generator (NPTRNG), also known as non-physical nondeterministic random bit generator is a true random number generator that does not have access to a dedicated hardware entropy source. NPTRNG uses a non-physical noise source that obtains entropy from system data, like outputs of application programming interface functions, residual information in the random access memory, system time or human input (e.g., mouse movements and keystrokes). A typical NPTRNG is implemented as software running on a computer. The NPTRNGs are frequently found in the kernels of the popular operating systems that are expected to run on any generic CPU. Reliability An NPTRNG is inherently less trustworthy than its physical random number generator counterpart, as the non-physical noise sources require specific conditions to work, thus the entropy estimates require major assumptions about the external environment and skills of an attacker. Typical attacks include: * vulnerab ...
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Random Number Generation
Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee. True random number generators can be ''Hardware random number generator, hardware random-number generators'' (HRNGs), wherein each generation is a function of the current value of a physical environment's attribute that is constantly changing in a manner that is practically impossible to model. This would be in contrast to so-called "random number generations" done by ''pseudorandom number generators'' (PRNGs), which generate numbers that only look random but are in fact predetermined—these generations can be reproduced simply by knowing the state of the PRNG. Various applications of randomness have led to the development of different methods for ...
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Entropy (computing)
In computing, entropy is the randomness collected by an operating system or application for use in cryptography or other uses that require random data. This randomness is often collected from hardware sources (variance in fan noise or HDD), either pre-existing ones such as mouse movements or specially provided randomness generators. A lack of entropy can have a negative impact on performance and security. Linux kernel The Linux kernel generates entropy from Keyboard (computing), keyboard timings, Mouse (computing), mouse movements, and integrated drive electronics (IDE) timings and makes the random character data available to other operating system processes through the special files /dev/random and /dev/urandom. This capability was introduced in Linux version 1.3.30. There are some Linux kernel patches allowing one to use more entropy sources. The audio_entropyd project, which is included in some operating systems such as Fedora (operating system), Fedora, allows audio data ...
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Randomness Extractor
A randomness extractor, often simply called an "extractor", is a function, which being applied to output from a weak entropy source, together with a short, uniformly random seed, generates a highly random output that appears Independent and identically distributed random variables, independent from the source and Uniform distribution (discrete), uniformly distributed. Examples of weakly random sources include radioactive decay or thermal noise; the only restriction on possible sources is that there is no way they can be fully controlled, calculated or predicted, and that a lower bound on their entropy rate can be established. For a given source, a randomness extractor can even be considered to be a true random number generator (Hardware_random_number_generator, TRNG); but there is no single extractor that has been proven to produce truly random output from any type of weakly random source. Sometimes the term "bias" is used to denote a weakly random source's departure from uniformi ...
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Atmospheric Noise
Atmospheric noise is radio noise, or "static", caused by natural atmospheric processes, primarily lightning discharges in thunderstorms. On a worldwide scale, there are about 40 lightning flashes per second, or lightning discharges per day. Lightning Atmospheric noise is radio noise caused by natural atmospheric processes, primarily lightning discharges in thunderstorms. It is mainly caused by cloud-to-ground flashes as the current is much stronger than that of Lightning#Cloud-to-cloud, cloud-to-cloud flashes. On a worldwide scale, 3.5 million lightning flashes occur daily. That means there are about 40 lightning flashes per second. The sum of all these lightning flashes results in atmospheric noise. It can be easily heard with any AM broadcasting, AM radio or single sideband, SSB radio receiver, receiver tuned to an unused frequency. The heard static is a combination of white noise (cumulative of distant thunderstorms) and electromagnetic interference, imp ...
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Springer International Publishing
Springer Nature or the Springer Nature Group is a German-British academic publishing company created by the May 2015 merger of Springer Science+Business Media and Holtzbrinck Publishing Group's Nature Publishing Group, Palgrave Macmillan, and Macmillan Education. History The company originates from several journals and publishing houses, notably Springer-Verlag, which was founded in 1842 by Julius Springer in Berlin (the grandfather of Bernhard Springer who founded Springer Publishing in 1950 in New York), Nature Publishing Group which has published '' Nature'' since 1869, and Macmillan Education, which goes back to Macmillan Publishers founded in 1843. Springer Nature was formed in 2015 by the merger of Nature Publishing Group, Palgrave Macmillan, and Macmillan Education (held by Holtzbrinck Publishing Group) with Springer Science+Business Media (held by BC Partners). Plans for the merger were first announced on 15 January 2015. The transaction was concluded in May 2015 with ...
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Nuclear Decay
Radioactive decay (also known as nuclear decay, radioactivity, radioactive disintegration, or nuclear disintegration) is the process by which an unstable atomic nucleus loses energy by radiation. A material containing unstable nuclei is considered ''radioactive''. Three of the most common types of decay are alpha, beta, and gamma decay. The weak force is the mechanism that is responsible for beta decay, while the other two are governed by the electromagnetic and nuclear forces. Radioactive decay is a random process at the level of single atoms. According to quantum theory, it is impossible to predict when a particular atom will decay, regardless of how long the atom has existed. However, for a significant number of identical atoms, the overall decay rate can be expressed as a decay constant or as a half-life. The half-lives of radioactive atoms have a huge range: from nearly instantaneous to far longer than the age of the universe. The decaying nucleus is called the parent ra ...
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Full Entropy
In cryptography, full entropy is a property of an output of a random number generator. The output has full entropy if it cannot practically be distinguished from an output of a theoretical perfect random number source (has almost bits of entropy for an -bit output). The term is extensively used in the NIST random generator standards NIST SP 800-90A and NIST SP 800-90B. With full entropy, the per-bit entropy in the output of the random number generator is close to one: 1-\epsilon, where per NIST a practical \epsilon<2^. Some sources use the term to define the ideal random bit string (one bit of entropy per bit of output). In this sense, "getting to 100% full entropy is impossible" in the real world.


Definition

The mathematical definition relies on a "distinguishing game": an adversary with unlimited computing power is provided with two sets of random numbers, each containing elements of length . One set is ''ideal'', it contains bit strings from the t ...
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Analog Device
Analog devices are a combination of both analog machine and analog media that can together measure, record, reproduce, receive or broadcast continuous information, for example, the almost infinite number of grades of transparency, voltage, resistance, rotation, or pressure. In theory, the continuous information in an analog signal has an infinite number of possible values with the only limitation on resolution being the accuracy of the analog device. Analog media are materials with analog properties, such as photographic film, which are used in analog devices, such as cameras. Example devices Non-electrical There are notable non-electrical analog devices, such as some clocks (sundials, water clocks), the astrolabe, slide rules, the governor of a steam engine, the planimeter (a simple device that measures the surface area of a closed shape), Kelvin's mechanical tide predictor, acoustic rangefinders, servomechanisms (e.g. the thermostat), a simple mercury t ...
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Random Seed
A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator. A pseudorandom number generator's number sequence is completely determined by the seed: thus, if a pseudorandom number generator is later reinitialized with the same seed, it will produce the same sequence of numbers. For a seed to be used in a pseudorandom number generator, it does not need to be random. Because of the nature of number generating algorithms, so long as the original seed is ignored, the rest of the values that the algorithm generates will follow probability distribution in a pseudorandom manner. However, a non-random seed will be cryptographically insecure, as it can allow an adversary to predict the pseudorandom numbers generated. The choice of a good random seed is crucial in the field of computer security. When a secret encryption key is pseudorandomly generated, having the seed will allow one to obtain the key. High entropy is importan ...
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