Hashingfunktioner

Hashingfunktioner, also known as hash functions, are mathematical algorithms that take an input, typically of arbitrary size, and produce a fixed-size output, known as a hash value or hash digest. This output is essentially a unique fingerprint for the input data. Hashing functions are designed to be deterministic, meaning that the same input will always produce the same output. They are also designed to be computationally efficient, allowing for quick generation of hash values.

The primary purpose of hashing functions is to ensure data integrity and security. By comparing the hash value of a piece of data with a stored or expected hash value, one can quickly verify if the data has been altered. Even a small change in the input data will result in a significantly different hash value, a property known as the avalanche effect. This makes them invaluable in applications like password storage, where storing the actual password is a security risk. Instead, only the hash of the password is stored. When a user attempts to log in, their entered password is hashed, and the resulting hash is compared to the stored hash.

Hashing functions are also used in data structures like hash tables, which allow for efficient searching, insertion, and deletion of data. Cryptographic hash functions, a specific type of hashing function, are designed with additional security properties, such as resistance to collision attacks (where two different inputs produce the same hash) and preimage attacks (where it is difficult to find an input that produces a given hash). Common examples of cryptographic hash functions include SHA-256 and MD5, though MD5 is now considered insecure for many cryptographic purposes due to known vulnerabilities.