Published on: 2025-06-09 07:04:35
Network Working Group D. Eastlake, 3rd Request for Comments: 4086 Motorola Laboratories BCP: 106 J. Schiller Obsoletes: 1750 MIT Category: Best Current Practice S. Crocker June 2005 Randomness Requirements for Security Status of This Memo This document specifies an Internet Best Current Practices for the Internet Community, and requests discussion and suggestions for improvements. Distribution of this memo is unlimited. Copyright Notice Copyright (C) The Internet Society (2005). Abstract Securit
Keywords: bits random randomness rfc security
Find related items on AmazonPublished on: 2025-07-19 05:56:12
When I recently looked at the state of the art in floating point random number generation, I was surprised to see a common procedure in many programming languages and libraries that is not really a floating-point algorithm: Generate a random integer with bits chosen based on the precision of the format. Convert to floating point. Divide to produce an output between 0 and 1. In code, this looks like: 1 func ( r * Rand ) Float64 () float64 { 2 int64 rand_int = r . Int63n ( 1 << 53 ) 3 return fl
Keywords: floating number numbers point random
Find related items on AmazonPublished on: 2025-08-25 18:01:46
This article was ported from my old Wordpress blog here, If you see any issues with the rendering or layout, please send me an email I have a little secret: I don’t like the terminology, notation, and style of writing in statistics. I find it unnecessarily complicated. This shows up when trying to read about Markov Chain Monte Carlo methods. Take, for example, the abstract to the Markov Chain Monte Carlo article in the Encyclopedia of Biostatistics. Markov chain Monte Carlo (MCMC) is a techniq
Keywords: distribution markov probability random walk
Find related items on AmazonPublished on: 2025-09-21 02:20:38
The cr.yp.to blog 2014.02.05: Entropy Attacks! The conventional wisdom says that hash outputs can't be controlled; the conventional wisdom is simply wrong. The conventional wisdom is that hashing more entropy sources can't hurt: if H is any modern cryptographic hash function then H(x,y,z) is at least as good a random number as H(x,y), no matter how awful z is. So we pile one source on top of another, hashing them all together and hoping that at least one of them is good. But what if z comes f
Keywords: entropy malicious random randomness source
Find related items on AmazonPublished on: 2025-10-08 22:05:45
17 min read Generative AI is reshaping many aspects of our lives, from how we work and learn, to how we play and interact. Given that it's Security Week, it's a good time to think about some of the unintended consequences of this information revolution and the role that we play in bringing them about. Today's web is full of AI-generated content: text, code, images, audio, and video can all be generated by machines, normally based on a prompt from a human. Some models have become so sophisticat
Keywords: code codeword image model pseudorandom
Find related items on AmazonPublished on: 2025-11-16 12:18:57
At V8, we're constantly striving to improve JavaScript performance. As part of this effort, we recently revisited the JetStream2 benchmark suite to eliminate performance cliffs. This post details a specific optimization we made that yielded a significant 2.5x improvement in the async-fs benchmark, contributing to a noticeable boost in the overall score. The optimization was inspired by the benchmark, but such patterns do appear in real-world code. The target async-fs and a peculiar Math.random
Keywords: heapnumber random seed slot value
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