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Hardware random number generator - Wikipedia, the free encyclopedia Random numbers generators can also be obtained from macroscopic phenomena, such as cards, dice, and the roulette wheel. "Random" numbers are also used for non-gambling purposes, both where their use is mathematically important, such as sampling for opinion polls, and in situations where "fairness" is approximated by randomization, such as selecting jurors and military draft lotteries. Another method for improving a near random bit stream is to exclusive-or the bit stream with the output of a high-quality cryptographically secure pseudo-random number generator such as Blum Blum Shub or a good stream cipher. en.wikipedia.org /wiki/Hardware_random_number_generator   (3115 words)

RFC 1750 (rfc1750) - Randomness Recommendations for Security Even if the random bits are generated as slowly as one per second and it is not possible to overlap the generation process, it should be tolerable in high security applications to wait 200 seconds occasionally. For example, assuming a few bits of randomness if the inter-keystroke interval is unique in the sequence up to that point and a similar assumption if the key hit is unique but assuming that no bits of randomness are present in the initial key value or if the timing or key value duplicate previous values. This amount of randomness is beyond the limit of that in the inputs recommended by the US DoD for password generation and could require user typing timing, hardware random number generation, or other sources. www.faqs.org /rfcs/rfc1750.html   (8904 words)

Citations: Pseudo-randomness and applications - Luby (ResearchIndex)   (Site not responding. Last check: 2007-10-21) Therefore if a user wants to enable other users 4 A pseudo random function is one that cannot be distinguished from a truly random one by a polynomialtime observer who is given access to the permutation in a fl box manner. The concept of a pseudo random function ensemble was introduced by Goldreich, Goldwasser and Micali [34] Loosely, this is an ecient function ensemble that cannot be e ciently distinguished from the uniform function ensemble by an adversary that has access to the functions as a fl box (see.... The concept of a pseudo random function ensemble was introduced by Goldreich, Goldwasser and Micali [28] Loosely, this is an efficient function ensemble that cannot be efficiently distinguished from the uniform function ensemble by an adversary that has access to the functions as a fl box.... citeseer.ist.psu.edu /context/47006/0   (2748 words)

Simulation Lecture Notes And randomness is a pretty good clay for forming other, non-random behavior. The histogram of outcomes from a uniform random variable should be flat. The one derived from a random sequence to which the difference outcome is compared. bluehawk.monmouth.edu /~rclayton/web-pages/s05-525/rng.html   (758 words)

[No title]   (Site not responding. Last check: 2007-10-21) RANDOMNESS AND PSEUDO-RANDOMNESS If computers are unable to generate true random numbers it is not suprising that they generate pseudo random numbers. For a stream of 1’s and 0’s to be considered statistically random there should be roughly equal numbers of 1s and 0s, equal numbers of 00s, 01s, 10s, and 11s and so on. BASIC PRNGs The most common method of generating pseudo random numbers is the use of linear and polynomial congruent generators, or the closely related linear shift register. vorlon.cwru.edu /~sbn/prng.doc   (956 words)

RFC 4086 (rfc4086) - Randomness Requirements for Security   (Site not responding. Last check: 2007-10-21) Even if the random bits are generated as slowly as one per second and it is not possible to overlap the generation process, it should be tolerable in most high-security applications to wait 200 seconds occasionally. Randomness Generation Examples and Standards Several public standards and widely deployed examples are now in place for the generation of keys or other cryptographically random quantities. Random data obtained from such a /dev/random device is suitable for key generation for long term keys, if enough random bits are in the pool or are added in a reasonable amount of time. www.faqs.org /rfcs/rfc4086.html   (13655 words)

Random Generators Random looking means that no probabilistic polynomial time algorithm can distinguish between true random bits and the output of the generator. Random number generation is used in a wide variety of cryptographic operations, such as key generation and challenge/response protocols. A random number generator is a function that outputs a sequence of 0s and 1s such that at any point, the next bit cannot be predicted based on the previous bits. www.softpanorama.org /Algorithms/random_generators.shtml   (3661 words)

[No title] WWW URL: http://www.usenix.org Network Randomization Protocol: A Proactive Pseudo-Random Generator Chee-Seng Chow Amir Herzberg IBM T.J. Watson Research Center Yorktown Heights, NY 10598 {cschow,amir}@watson.ibm.com Abstract A major security threat to any security solutions based on a centralized server is the possibility of an adversary gaining access to and taking control of the server. There are many pitfalls in using supposedly random sources in a computer (such as disk access times and system clocks) as a source of randomness. The sampler gets random values from the server (using the client-server interface to be described in the next section) and combines them with the clock readings (using DES for mixing). www.usenix.org /publications/library/proceedings/security95/full_papers/chow.txt   (5786 words)

Random Reality And randomness comes into play in quantum theory--when a particle such as an electron is observed, its properties are randomly selected from a set of alternatives predicted by the equations. Chaitin defined random truths as ones that cannot be derived from the axioms of a given formal system. The chilling conclusion, wrote Chaitin in New Scientist, is that randomness is at the very heart of pure mathematics (A Random Walk). www.fortunecity.com /emachines/e11/86/randreal.html   (3085 words)

Einführung zu Csound random Generators Randomness in nature, errors in the performance of a classical musician, arbitrariness of an improviser, and similarly most types of "noise" in physical events (such as thunder, background car traffic, an anthill or wheeze in a flute tone) cannot be represented directly in mathematics. Apart from the opcodes designed to generate random values, there are a couple of recent ones for pink noise, and some opcodes that use random values internally. Since random values are accumulated and added to the output the cycle length variation is not clear to this author, but it can be much longer than that of the internal PRNG. csounds.com /ezine/summer2001/noise   (2821 words)

Probabilistic method -- Facts, Info, and Encyclopedia article   (Site not responding. Last check: 2007-10-21) If the probability that the random thing satifies certain properties is greater than zero, then this proves the existence of a thing that satisfies the properties. If it can be shown that the random variable can take on a value less than the expected value, this proves that the random variable can also take on some value greater than the expected value. For any S, the (The sum of the values of a random variable divided by the number of values) expected value of X(S) is simply the probability that all of the r(r − 1)/2 edges in S are the same color, www.absoluteastronomy.com /encyclopedia/p/pr/probabilistic_method.htm   (862 words)

True random numbers generator: Basic source code, algorithm The randomization seed is highly random; therefore the next sequence of (set) of numbers is unpredictable. The degree of randomness was far higher than what the much faster PCs gave me. Now, delaying the random generation does improve the degree of randomness. Of course, if using the TIMER only as the seed and running the random generator at the same time of the day, the sequence of numbers will be always the same. www.saliu.com /random-numbers.html   (2015 words)

Pseudorandom Number Generators   (Site not responding. Last check: 2007-10-21) By generating bits with a computationally complex process it is possible to produce a sequence of random bits that are cryptographically secure. With three-quarters of the random value determined the only unknown is microseconds, which with only a million values yields easily to brute force [5]. As the demand for truly random numbers increases it seems likely that software based PRNGs may be replaced with hardware based RNGs. vorlon.cwru.edu /~sbn/prng2.html   (657 words)

5.4 Pseudo-randomness. The problem is not that making a true random generator is impossible: we just saw efficient ways to perfect the distributions of biased random sources. With a truly random generator, one actually has to record all its outcomes: long and costly. be the probabilities of acceptance of r0x and r1x for random r of length i-1. www.cs.bu.edu /fac/lnd/toc/z/node24.html   (407 words)

CGTalk - ranDomNeSS...or not With my limited understanding of such things, I thought that computers don't really do real randomness, but rather a sort of pseudo randomness, or a pattern generated by an algorithm to simulate randomness. It would be SWEET, if when a "random" element is required, rather than dipping into the fl box of platform dependant randomness, why not allow us to specify our own flavor of SLA as a pseudo-random data source. SLA noises could be used as gray-scale pseudo-random gradients to generate source data to give the impression of randomness. forums.cgsociety.org /printthread.php?t=23670   (483 words)

Special Year: Topics This insight, that hardness can be turned into randomness, has led to some surprising and deep connections between the complexity of randomness, cryptography, circuit complexity and combinatorics. The extensive technical progress of the last couple of years on different ways of constructing pseudo-random generators still has to be fully understood, simplified and generalized to realize its potential impact on this and related problems. The behaviour of a proof system on random tautologies is traditionally considered as a good indicator of its strength. www.math.ias.edu /csdm/00-01/topics.html   (2709 words)

The Hardware Random Number Generator Randomness may be gathered from an RMS voltage of about 4kTRB, where B is the bandwidth, R is the resistance, T is temperature, and k is Boltzman's constant. The major source of randomness of this RNG is the unsynchronized nature of multiple oscillators with randomly changing frequencies. It follows that any efficient randomized algorithms maintains its performance when its internal coin tosses are substituted by a sequence generated by a pseudorandom generator. www.ciphersbyritter.com /NEWS4/HARDRAND.HTM   (19063 words)

ITworld.com - JAVA SECURITY - Faster Random Numbers It seeds the pseudo-random number generator with a random value derived from thread timings. Many operating systems provide a source of security-grade randomness for use by operating system tasks and applications. This source of randomness is often faster than Sun's algorithm. www.itworld.com /nl/java_sec/09072001/pf_index.html   (231 words)

Local Randomness in Pseudo-random Sequences - Maurer, Massey (ResearchIndex)   (Site not responding. Last check: 2007-10-21) The cryptanalyst is assumed to have in#nite computational resources and hence the security of the generators does not rely on any unproved hypothesis about the di#culty of solving a certain problem, but rather relies on the assumption that the number of bits of the generated sequence the enemy can access is limited. ...a truly random function as long as it is evaluated for at most k arguments. 1 the construction of random number generators and random func.. citeseer.ist.psu.edu /maurer91local.html   (419 words)

Chris Umans Research Summary The use of randomness is pervasive in modern algorithm design and other settings. One of the fundamental questions of Complexity Theory asks whether randomness is indeed essential: is it the case that there are some problems with efficient randomized solutions but no efficient deterministic solution, or is there some way to "compile" every efficient randomized algorithm into an efficient deterministic algorithm ("derandomize" the algorithm). For example, while a random bounded-degree graph is easily seen to be an expander, the well-known LPS expander graph construction relies on deep mathematical results. www.cs.caltech.edu /~umans/summary.htm   (930 words)

Introduction All this pessimism in estimating randomness could lead to the operator having to type slightly longer, but it usually still only requires the operator to type some dozens of keys, which takes somewhere between five and ten seconds, which should be no trouble at all. It has no options that can influence the gathering of randomness, does not log any of the internal numbers, reducing the chance of a clerical error that could publish it, and is limited to dealing 100 boards, enough for the longest session. The randomness gathered from the environment is usually used as a seed. www.xs4all.nl /~sater/doc.html   (5301 words)

[No title] The problem is {\em not} that making a true random generator is impossible: we just saw efficient ways to perfect the distributions of biased random sources. By Kolmogorov's standards, pseudo-random strings are not random: let $G$ be the generator; $s$ be the seed, $G(s) = S$, and $S\gg k=s$. Let $P_0(x)$ and $P_1(x)$ be the probabilities of acceptance of $r0x$ and $r1x$ for random $r$ of length $i-1$. www.cs.bu.edu /fac/lnd/toc/s-pseud   (626 words)

[No title]   (Site not responding. Last check: 2007-10-21) Complexity theory suggests two approaches as to how to obtain such bits: The first approach is to construct pseudo-random generators, (algorithms which are able to produce distributions which look random to small circuits, and thus to probabilistic algorithms). Such constructions are known if one is allowed to assume the existence of functions which are hard to compute for small circuits. The second approach is to construct extractors (algorithms which are able to transform imperfect randomness that can be found in nature into perfect randomness that is suitable to run probabilistic algorithms). www.math.technion.ac.il /~techm/20011028110020011028sha   (217 words)

Bellairs: Pseudo-Random Unitary Operators   (Site not responding. Last check: 2007-10-21) Emerson, Weinstein, Saraceno, Lloyd and Cory have explored the possibility of approximating the Haar measure by randomly applying gates drawn from a universal set. Recently, Buhrman, Hayden and Christandl have shown that the correlation locking effect can be implemented against an adversary with a polynomial time quantum computer using mutually unbiased bases instead of random unitary encodings. In keeping with the objective of the workshop, there will be two sets of lectures, one a crash course in classical pseudo-randomness and the other devoted to proposals for quantum pseudo-random operators and their applications. www.cs.mcgill.ca /~patrick/bellairs2005   (237 words)

rndseq random notes and various noises on their instruments. Oriental musicians, on the contrary, consider unplanned random events triangular waveform's frequency and the range of randomness exhibited www.angelfire.com /music2/theanalogcottage/rndseq.htm   (845 words)

Randomness resources for Dr. Dobb's Journal readers   (Site not responding. Last check: 2007-10-21) Recently Ian Goldberg and I wrote an article for Dr. Dobb's Journal entitled Randomness and the Netscape Browser. We built a list of online resources for generating crypto-strength randomness, as promised in the article. www.cs.berkeley.edu /~daw/netscape-randomness.html   (73 words)

Counting Complexity and Computational Group Theory   (Site not responding. Last check: 2007-10-21) We therefore survey some of the different applications of the assumption and the current knowledge on its security. Furthermore, we show a randomized reduction of the worst-case DDH-Assumption to its average case (based on the random-self-reducibility of the DDH-Problem that was previously used by Stadler [Stad]). We consider our research of the DDH-Assumption to be of independent importance given that the assumption was recently used in quite a few interesting applications (e.g., [CS]). www.eccc.uni-trier.de /eccc-local/ECCC-Theses/reingold.html   (738 words)

[No title]   (Site not responding. Last check: 2007-10-21) Title: Simple extractors for all min-entropies and a new pseudo-random generator Joint work with Chris Umans from Microsoft research Abstract: We present a simple, self-contained extractor construction that produces good extractors for all min-entropies (min-entropy measures the amount of randomness contained in a weak random source). Our construction is algebraic and builds on a new polynomial-based approach introduced by Ta-Shma, Zuckerman, and Safra and avoids complicated recursions, iterations, and compositions that characterized much of the previous work. Our construction also yields {\em optimal} hitting set generators closing the gap left by previous constructions. www.cs.huji.ac.il /~theorys/2002/Ronen_Shaltiel   (158 words)

Somewhat pseudo-randomness some other random poeple I know: (no, not all of them!) Info on ZOO, the new UNIX computing cluster being implemented at UVM Random things you can use with microsoft windows. www.uvm.edu /~jdion/personal/random.html   (370 words)

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