A hashing algorithm is a function that takes an input (often referred to as a “message”) and returns a fixed-size string of bytes, typically a “digest” that is unique to that input. The main purpose of a hashing algorithm is to transform data into a fixed-size value (hash value), regardless of the input size.
Key Properties of Hashing Algorithms:
- Deterministic: The same input will always produce the same output.
- Fixed-Length Output: Regardless of the size of the input data, the output (hash) has a fixed length. For example, SHA-256 always produces a 256-bit hash.
- Efficient: It should be computationally easy to compute the hash for any given input.
- Pre-image Resistance: Given a hash, it should be computationally infeasible to reverse-engineer the original input.
- Collision Resistance: It should be unlikely (though not impossible) to find two different inputs that produce the same hash.
- Avalanche Effect: A small change in the input should produce a significantly different hash.
Common Hashing Algorithms:
- MD5: 128-bit hash value, now considered weak due to vulnerability to collision attacks.
- SHA-1: 160-bit hash, also considered broken due to collision vulnerabilities.
- SHA-256: Part of the SHA-2 family, it produces a 256-bit hash and is widely used.
- SHA-3: A more recent family of hashing algorithms, designed to offer additional security.
Uses of Hashing:
- Data Integrity: Verifying that data hasn’t been altered (e.g., checksums, file verification).
- Cryptography: Hashing is used in digital signatures, password storage (hashing passwords before storing them), and blockchain (e.g., Bitcoin uses SHA-256).
- Data Structures: Hashing is used in data structures like hash tables for fast data retrieval.
- Digital Fingerprints: Creating unique identifiers for data, files, or messages.
Hashing plays a crucial role in security, integrity verification, and efficient data processing.