Hashing 🔍

Introduction to Hashing 🧩

• Definition: Hashing is a process that takes an arbitrary input and maps it to a fixed-size output, known as a hash or digest.

• Output Size: The size of the hash is constant and specified in bits, regardless of the input size.

• Uniqueness: Ideally, each unique input should produce a unique hash.

Applications 🛠️

• Hash Tables: Used in data structures to speed up data lookups.

• Data Deduplication: Identifies and removes duplicate datasets to save space.

• Database Indexing: Speeds up searches and data retrieval.

Cryptographic Hash Functions 🔒

• Purpose: Used for security-related tasks such as authentication, message integrity, fingerprinting, and digital signatures.

• Characteristics:

  • One-Directional: Impossible to reverse the function to recover the original input.

  • Deterministic: Same input always produces the same hash.

  • Efficient: Quick to compute.

  • Small Changes: A small change in input results in a completely different hash output.

  • Collision-Resistant: Prevents two different inputs from producing the same output.

Comparison with Symmetric Encryption 🔐

• Similarities: Both operate on blocks of data. Many hash functions are based on modified block ciphers.

• Differences: Hashing is one-way and does not allow recovery of the original data, unlike encryption which is reversible with the right key.

Example 💡

• Imaginary Hash Function:

  • Input: "Hello World"

  • Hash Output: E49AOOFF

  • Input: "hello world" (with slight modification)

  • Hash Output: FF1832AE

• Real Hash Function Example:

  • Using md5sum on the input "Hello World" produces a consistent hash digest.

Summary 📜

• Hashing maps data to a fixed-size output, crucial for various computing applications.

• Cryptographic Hash Functions provide security features like non-reversibility and collision resistance.

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