PETEROUPC . GITHUB . IO {}

Analyzed Page
Matching Content Categories
CMS
Monthly Traffic Estimate
How Does Peteroupc.github.io Make Money
Keywords
Topics
Questions
Social Networks
External Links
CDN Services

We are analyzing https://peteroupc.github.io/random.html.

Title:
Random Number Generator Recommendations for Applications
Description:
No description found...
Website Age:
12 years and 3 months (reg. 2013-03-08).

Matching Content Categories {📚}

Technology & Computing
Mobile Technology & AI
Cryptocurrency

Content Management System {📝}

What CMS is peteroupc.github.io built with?

Custom-built

No common CMS systems were detected on Peteroupc.github.io, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of peteroupc.github.io audience?

🚦 Initial Traffic: less than 1k visitors per month

Based on our best estimate, this website will receive around 138 visitors per month in the current month.

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How Does Peteroupc.github.io Make Money? {💸}

We don’t know how the website earns money.

The purpose of some websites isn't monetary gain; they're meant to inform, educate, or foster collaboration. Everyone has unique reasons for building websites. This could be an example. Peteroupc.github.io might be plotting its profit, but the way they're doing it isn't detectable yet.

Keywords {🔍}

prng, random, seed, rng, numbers, number, application, prngs, rngs, cryptographic, pseudorandom, hash, functions, noise, unique, generate, bits, randomness, generating, highquality, process, generation, document, manuallyseeded, game, applications, integers, data, identifiers, function, output, generated, security, noncryptographic, sources, including, include, state, nondeterministic, code, reproducible, bit, generators, time, information, examples, programming, entropy, independent, generator,

Topics {✒️}

commons/commons-rng-simple artifact manually-seeded high-quality prng �full-period” linear prng �fast-key-erasure” generator manually-seeded prngs include uniform random-behaving integers manually-seeded prng recommendations nitty-gritty technical details” �post-spectre threat model multiplying floating-point numbers pseudo-random number generators” �pseudo-random number generators �verifiable delay functions” verifiable delay functions cases manually-seeded prngs rng topics generates random-behaving numbers avoid floating-point numbers random-number-csprng package generating random-behaving numbers procedural noise generation produce floating-point numbers monte carlo estimations generate floating-point numbers maps n-bit integers popular programming languages verifiable random numbers manually-seeded prngs correctly guessing prior linear congruential generators functional programming languages programming languages offer high-resolution counter values general-purpose computing devices unique n-bit integer functions include pbkdf2 unkeyed hash functions write hash functions developed hash functions manually-seeded prng” manually-seeded prng �shrinking generator” technique pseudorandom functions deliberately noise functions deliver random-behaving numbers requirements high-quality rngs cryptographic hash functions random-behaving number dsi/dsiutils artifact long-term key

Questions {❓}

Can the application easily check identifiers for uniqueness within the desired scope and range (for example, check whether a file or database record with that identifier already exists)31?
Can the application tolerate the risk of generating the same identifier for different resources32?
Do identifiers have to be hard to guess, be simply “random-looking”, or be neither?
Do identifiers have to be memorable?
Do identifiers have to be typed in or otherwise relayed by customers33?
Does the application run multiple independent processes that use pseudorandom numbers?
Does the application use random-behaving numbers for information security purposes (for example, as passwords or other secrets)5?
Is the resource an identifier identifies available to anyone who knows that identifier (even without being logged in or authorized in some way)?
No: Does the application require reproducible “random” numbers?
No: Is a cryptographic RNG too slow for the application?
What Is Entropy?
What Is a Nondeterministic Source?