# cryptographically secure pseudo-random number generator

> pseudorandom number generator with good statistical randomness and resistance to cryptanalysis

**Wikidata**: [Q1790389](https://www.wikidata.org/wiki/Q1790389)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Cryptographically_secure_pseudorandom_number_generator)  
**Source**: https://4ort.xyz/entity/cryptographically-secure-pseudo-random-number-generator

## Summary
A cryptographically secure pseudo-random number generator (CSPRNG) is a specialized algorithm designed to produce numbers that appear random but are actually deterministic, with strong statistical randomness and resistance to cryptanalysis. It serves as a fundamental cryptographic primitive used for generating keys, initialization vectors, nonces, and salts in secure systems.

## Key Facts
- **Class**: A subclass of both pseudorandom number generators and cryptographic primitives.
- **Uses**: Cryptography, key generation, initialization vectors, nonces, and salts.
- **Aliases**: Includes acronyms like CSPRNG and various language-specific terms.
- **Related Entities**: Linked to cryptography, ISAAC (1993), Dual_EC_DRBG, and CryptGenRandom.
- **Standards**: Referenced in RFC 1750 and RFC 4086 for randomness recommendations.
- **Wikipedia Coverage**: Available in 10 languages, including English, Spanish, and Japanese.
- **Wikidata ID**: /m/018x4l, referenced in 2013.
- **Category**: Part of the "Cryptographically secure pseudo-random number generator" category on Wikipedia.

## FAQs
### Q: What makes a CSPRNG different from a regular PRNG?
A: A CSPRNG is designed with cryptographic security in mind, ensuring resistance to attacks and predictable patterns, whereas regular PRNGs prioritize speed and simplicity.

### Q: Where are CSPRNGs commonly used?
A: CSPRNGs are used in cryptography for generating keys, initialization vectors, nonces, and salts to ensure secure communication and data protection.

### Q: What are some well-known CSPRNG algorithms?
A: Notable examples include ISAAC (1993) and Dual_EC_DRBG, though the latter has faced controversy due to its design.

### Q: How do CSPRNGs ensure security?
A: They rely on strong statistical properties and resistance to cryptanalysis, often incorporating entropy sources and rigorous mathematical foundations.

### Q: What standards guide CSPRNG development?
A: RFC 1750 and RFC 4086 provide recommendations for randomness requirements in secure systems.

## Why It Matters
Cryptographically secure pseudo-random number generators are essential for modern cryptography, ensuring the security of digital communications, authentication systems, and data encryption. Without CSPRNGs, cryptographic systems would be vulnerable to attacks that exploit predictable patterns in random number generation. These algorithms underpin the integrity of secure transactions, digital signatures, and encryption protocols, making them critical for cybersecurity and privacy. Their ability to produce seemingly random yet deterministic outputs is foundational for creating robust cryptographic keys and initializing secure processes.

## Notable For
- **Cryptographic Primitive**: Serves as a building block for more complex cryptosystems.
- **Resistance to Analysis**: Designed to withstand cryptanalysis, unlike general-purpose PRNGs.
- **Widespread Use**: Integral to key generation, initialization vectors, and other security-critical applications.
- **Standards Compliance**: Referenced in RFCs for randomness recommendations.
- **Language Support**: Documented in multiple languages, indicating broad relevance.

## Body
### Definition and Purpose
A cryptographically secure pseudo-random number generator (CSPRNG) is a deterministic algorithm that produces sequences of numbers that appear random. Unlike regular pseudorandom number generators, CSPRNGs are designed to resist cryptanalysis, ensuring that their outputs cannot be predicted or manipulated by adversaries.

### Applications
CSPRNGs are used in cryptography for:
- **Key Generation**: Creating secure encryption keys.
- **Initialization Vectors**: Ensuring unique starting points for encryption processes.
- **Nonces**: Unique values used in cryptographic protocols to prevent replay attacks.
- **Salts**: Random values added to passwords to enhance security.

### Related Technologies
- **ISAAC**: A cryptographic number generator developed in 1993.
- **Dual_EC_DRBG**: A controversial pseudorandom number generator.
- **CryptGenRandom**: A cryptographic algorithm used in Windows systems.

### Standards and Documentation
- **RFC 1750**: Provides randomness recommendations for security.
- **RFC 4086**: Outlines randomness requirements for secure systems.

### Wikipedia and Wikidata
- **Wikipedia Title**: "Cryptographically secure pseudorandom number generator."
- **Languages**: Available in 10 languages, including Catalan, German, and Japanese.
- **Wikidata Description**: "Pseudorandom number generator with good statistical randomness and resistance to cryptanalysis."

## Schema Markup
```json
{
  "@context": "https://schema.org",
  "@type": "Thing",
  "name": "Cryptographically secure pseudo-random number generator",
  "description": "A deterministic algorithm producing sequences of numbers that appear random, designed for cryptographic security.",
  "sameAs": [
    "https://www.wikidata.org/wiki/Q15241312",
    "https://en.wikipedia.org/wiki/Cryptographically_secure_pseudorandom_number_generator"
  ],
  "additionalType": "CryptographicPrimitive"
}

## References

1. Freebase Data Dumps. 2013