search for: pseudorandom

Hello, It seems that there is a small probability of collisions among uuid''s produced by uuidtools'' UUID.random_create() running in concurrent user processes on a host (fcgi)? The ~2 bytes extracted from the randomized clock_sequence make a collision unlikely. http://rubyforge.org/frs/download.php/8572/uuidtools-1.0.0.zip Do I miss something? DD -- Posted via

...e why you need this feature. You can provide LLVM with a > SEED value that can be controlled from the command line. A wrapper (such > as a build-script) can control this value. (disclaimer: I was a member of Stephen's research group and worked on this project.) To my knowledge, the pseudorandom number generator in LLVM is not cryptographically secure. In this use case, the intent is to make it difficult to get the random number seed or the generator's state at any point in the random number stream by looking at the output. If the state of the generator can be compromised, then an at...

...can provide LLVM with a >> SEED value that can be controlled from the command line. A wrapper (such >> as a build-script) can control this value. > > > (disclaimer: I was a member of Stephen's research group and worked on > this project.) > > To my knowledge, the pseudorandom number generator in LLVM is not > cryptographically secure. In this use case, the intent is to make it > difficult to get the random number seed or the generator's state at any > point in the random number stream by looking at the output. If the state > of the generator can be com...

...entry=2) at ../lib/util/genrand.c:46 The above is deliberate. open of /dev/urandom should never fail. If it does we have worse problems :-). https://en.wikipedia.org/wiki//dev/random "In Unix-like operating systems, /dev/random, /dev/urandom and /dev/arandom are special files that serve as pseudorandom number generators. They allow access to environmental noise collected from device drivers and other sources.[1] /dev/random typically blocks if there is less entropy available than requested; /dev/urandom typically never blocks, even if the pseudorandom number generator seed was not fully initializ...

...ommy sample_wrapper <- function() { # initialize a variable to pass to C++ init_var <- runif(1) # get current state of RNG stream # first entry of .Random.seed is an integer representing the algorithm used # second entry is current position in RNG stream # subsequent entries are pseudorandom numbers seed_pos <- .Random.seed[2] seed <- .Random.seed[seed_pos + 2] out <- sample_cpp(init_var = init_var, seed = seed) # move R's position in the RNG stream forward by 1 with a throw away sample runif(1) # return the output out} [[alternative HTML version delete...

...ough I am basically not an R user, I have installed version 3.3.1 and am also the author of a statistics program written in Visual Basic that contains a component which correctly implements the Mersenne Twister (MT) algorithm. I believe that it is not possible to generate the correct stream of pseudorandom numbers using the MT default random number generator in R, and am not the first person to notice this. Here is a posted 2013 entry (www.r-bloggers.com/reproducibility-and-randomness/) on an R website that asserts that the SAS computer program implementation of the MT algorithm produces differ...

I have a new centos 6 install. Randomly i get out of memory messages and my ssh file transfer dies. I have tried this in filezilla as well as winscp. I have disabled motd in ssh and i also had entropy problems so i enacted rngd -r /dev/urandom -o /dev/random but did not stop the out of memory errors. I am seeing the below in the logs. It only occurs during ssh file transfers. Feb 28

...pass to C++ > > init_var <- runif(1) > > > > # get current state of RNG stream > > # first entry of .Random.seed is an integer representing the > algorithm used > > # second entry is current position in RNG stream > > # subsequent entries are pseudorandom numbers > > seed_pos <- .Random.seed[2] > > > > seed <- .Random.seed[seed_pos + 2] > > > > out <- sample_cpp(init_var = init_var, seed = seed) > > > > # move R's position in the RNG stream forward by 1 with a throw away > sample...

Hello for my password recovery system I want to recover the users password and send it to them. In the DB its saved via SHA1 (login generator) -- Posted via http://www.ruby-forum.com/.

Hi, I maintain Kodi[1] in RPMFusion[2] and the latest version of Kodi, 18.0, is crashing when trying to browse the SMB network. The previous version, 17.x, worked fine. The backtrace shows that Samba was not able to open /dev/urandom, which can't be true and must be masking another issue. The issue occurs on any Fedora 28 or 29 system (multiple user reports[3]). SELinux is disabled and

...e to make it possible for ssh-rand-helper to fall back to external commands if PRNGD cannot be reached, instead of choosing one or the other at compile time? - When using PRNGD, the program gets 48 bytes of entropy from PRNGD, stirs it into OpenSSL's RAND_add(), and outputs 48 bytes of pseudorandom bytes based on this entropy. Does this present any advantage over just dumping the 48 bytes of entropy received from PRNGD directly? The semantics I'm envisioning here: Define USE_PRNGD, USE_CMDS, or both. Case 1: USE_PRNGD && USE_CMDS: read_seedfile() fetch...

..._set reproduces this. Later versions switched to 5489 as the default seed, you can choose this explicitly via gsl_rng_set instead if you require it. For more information see, Makoto Matsumoto and Takuji Nishimura, ?Mersenne Twister: A 623-dimensionally equidistributed uniform pseudorandom number generator?. ACM Transactions on Modeling and Computer Simulation, Vol. 8, No. 1 (Jan. 1998), Pages 3?30 The generator gsl_rng_mt19937 uses the second revision of the seeding procedure published by the two authors above in 2002. The original seeding procedures could ca...

Hi Stephen, > Greetings LLVM Devs! > > I am a PhD student in the Secure Systems and Software Lab at UC > Irvine. We have been working on adding randomness into code generation > to create a diverse population of binaries. This diversity prevents > code-reuse attacks such as return-oriented-programming (ROP) by > denying the attacker information about the exact code layout.

...4. In R: post-process the results from the transformed space back to the space of the parameters I'm estimating. 5. Still in R: call stats::runif to change the position in R's RNG stream so that if the user calls the function 2 times in a row without setting the seed, they'll still get pseudorandom results by providing the C++ RNG with a different seed. So, a single call to the user-facing function results in many many draws from both RNG streams. The true "problem" spawning my question is that I'd like my users to be able to reproduce their results and calling set.seed() once...

...r, I have installed version 3.3.1 >> and am also the author of a statistics program written in Visual Basic >> that contains a component which correctly implements the Mersenne >> Twister (MT) algorithm. I believe that it is not possible to generate >> the correct stream of pseudorandom numbers using the MT default random >> number generator in R, and am not the first person to notice this. Here >> is a posted 2013 entry >> (www.r-bloggers.com/reproducibility-and-randomness/) on an R website >> that asserts that the SAS computer program implementation of t...

...ndom is blocking due to insufficient entropy, feeding false entropy in from urandom buys you nothing, other than to fool /dev/random into thinking it has more entropy than it actually does. On a typical Linux system, /dev/random and /dev/urandom get their entropy from the same source, so feeding pseudorandom numbers from one to the other is essentially lying to the kernel; it will get its revenge on you for that lie, eventually. rngd is only useful when reading from a [P]RNG that the kernel isn?t already using for entropy, such as a hardware RNG. > but did not stop the out of memory errors. Why w...

wforce is the username always. auth_policy_hash_nonce should be set to a pseudorandom value that is shared by your server(s). Weakforced does not need it for anything. auth_policy_server_api_header should be set to Authorization: Basic <echo -n wforce:our_password | base64> without the < >. Aki On 6.3.2019 20.42, Robert Kudyba via dovecot wrote: > I took suggestio...

...gt; # initialize a variable to pass to C++ > init_var <- runif(1) > > # get current state of RNG stream > # first entry of .Random.seed is an integer representing the algorithm used > # second entry is current position in RNG stream > # subsequent entries are pseudorandom numbers > seed_pos <- .Random.seed[2] > > seed <- .Random.seed[seed_pos + 2] > > out <- sample_cpp(init_var = init_var, seed = seed) > > # move R's position in the RNG stream forward by 1 with a throw away sample > runif(1) > > # retu...

How many distinct values can rnorm return? I assume that rnorm manipulates runif in some way, runif uses the Mersenne Twister, which has a period of 2^19937 - 1. Given that runif returns a 64 bit precision floating point number in [0,1], the actual period of the Mersenne Twister in a finite precision world must be significantly less. One of the arguments for Monte Carlo over the bootstrap is

Is there a way to generate identical random samples using R's runif function and SAS's ranuni function? I have assigned the same seed values in both software packages, but the following results show different results. Thanks! R === > set.seed(6) > random <- runif(10) > random [1] 0.6062683 0.9376420 0.2643521 0.3800939 0.8074834 0.9780757 0.9579337 [8] 0.7627319 0.5096485