What is Hashing?

Hashing is a process that converts an input (often referred to as a key) into a fixed-size string of characters, using a specific algorithm known as a hash function. Regardless of the original amount of data or file size involved, its unique hash will always be the same size.

Components of Hashing

Key

The key is the input data that is fed into the hash function. It can be in any format such as text, numbers, images, or files.

Hash Function

The hash function takes the key as input and returns a hash value. The hash function is the central part of the hashing process. Popular hashing algorithms work with block sizes between 160 and 512 bits.

Hash Value

The output of the hash function is the hash value. Ideally, each input should produce a unique hash value. These hash values can be used for data authentication or digital signatures, or they can be stored for easy lookup in a hash table

How Does Hashing Work?

Typically, hash functions take inputs of variable lengths and return outputs of a fixed length. A cryptographic hash function combines the message-passing capabilities of hash functions with security properties. For example, Secure Hashing Algorithm 256 (SHA-256) converts the input it receives into binary, creates hash values, initializes constants, chunks data into bits, creates a message schedule, runs a compression loop, and modifies the final values.

Hash functions are deterministic, meaning they will produce the same result each time the same input is used. For instance, the word "Hello" will produce an output that is the same number of characters (64) as "Hello world" and "Hello John." However, the hash will be significantly different for all three.

Properties of Hash Functions

Cryptographic hash functions exhibit certain properties:

Collision-free: This means that no two different input hashes should map to the same output hash.

Hidden: It is difficult to guess the input value for a hash function from its output.

Puzzle-friendly: It should be difficult to select an input that provides a predefined output. Thus, the input should be selected from a distribution that's as wide as possible.

Properties of Hashing Algorithms

Hashing algorithms have certain properties:

i. Quick computation: Effective hashing algorithms quickly process any data type into a unique hash value.

ii. Detecting changes in data: Hashing is an effective way to compare two sets of data and see if they're different. This property makes hashing useful for detecting errors and changes in data.

iii. Data privacy: Hashing is often used to store sensitive information like passwords. Instead of storing the actual password, the system stores the hash value of the password.

iv. Database management: Hashing can simplify the management of large databases. Instead of relying on an index structure, hashing allows you to search for a data record using a search key and hash function

Hash Collision

A hash collision occurs when two different keys produce the same hash value. This situation needs to be handled using some collision handling technology. Methods for resolving hash collisions include open addressing (closed hashing) and separate chaining (open hashing).

Hashing in Computing Systems

Hash functions are commonly used data structures in computing systems for tasks such as checking the integrity of messages and authenticating information. They add security features, making detecting the contents of a message or information more difficult.

Hashing is also essential to blockchain management in cryptocurrency. Because of the features of a hash, they are used extensively in online security—from protecting passwords to detecting data breaches to checking the integrity of a downloaded file.

Hashing in Practice

For example, consider you want to store the string "Rachel" you apply a hash function to that string to get a memory location. The function may return 10 for the input "Rachel" so assuming you have an array of size 100 you store "Rachel" at index 10. If you want to retrieve that element you just call GetmyHashFunction("Rachel") and it will return 10. If the hash function is well implemented it will be in constant time O(c), meaning you don't have to traverse all the elements stored in the hash table. You will get the element "instantly".

Benefits of Hashing

There are many benefits of hashing, including modern-day cryptography hash functions. Some of these benefits are:

i. Data Retrieval: Hashing uses algorithms to map object data to an integer value. A hash is beneficial because it can be used to narrow down searches when locating items on the object data map.

ii. Password Security: Creating strong passwords is an effective way of keeping intruders at bay. One of the benefits of hashing is that its password cannot be modified, stolen, or changed. If the hash code is stolen, it will be useless because it cannot be applied anywhere else.

iii. Message and data authentication: Hashing helps ensure that data isn't intercepted between the sender and the recipient. It's a way to authenticate data or show that the data received wasn't somehow changed along the way.

iv. Blockchain: In a blockchain, every new record or transaction is known as a block. Each block includes the hash value of the data in the previous block. If someone tries to alter the transaction history, the hash values would change, rendering the transaction invalid.

v. Database management: Hashing allows you to search for a data record using a search key and hash function. There are two hashing methods you can use in a database management system (DBMS): Static hashing and dynamic hashing.

vi. Cyclic Redundancy Check (CRC): When the primary purpose of hashing is simply to detect errors and changes in data, then most people work with a CRC code.

Conclusion

Understanding the concept of hashing is crucial for anyone working in areas such as data science, backend development, or cybersecurity. It's a powerful tool for data authentication, security, and database management