Hashing

What Does Hashing Mean?

Hashing is the process of translating a given key into a code to map data. A hash function is used to substitute the information with a newly generated hash code. More specifically, hashing is the practice of taking a string or input key, a variable created for storing narrative data and representing it with a hash value, which is typically determined by an algorithm and constitutes a much shorter string than the original.

The hash table creates a list where all value pairs are stored and easily accessed through its index. The result is a technique for accessing key values in a database table in a very efficient manner as well as a method to improve the security of a database through encryption.

Table of Contents Table of Contents

1. What Does Hashing Mean?
2. Key Takeaways
3. How Hashing Works
4. Types of Hashing Algorithms
5. Hashing vs. Encryption
6. Hashing in Computer Science and Encryption
7. Using Hashing in Database Retrieval
8. Hashing's Role in File Tampering
9. Hashing Uses
10. Hashing in Cybersecurity
11. ?Hashing Pros & Cons
12. The Bottom Line
13. FAQs

Show Full Guide

Table of Contents

1. What Does Hashing Mean?
2. Key Takeaways
3. How Hashing Works
Show Full Guide
4. Types of Hashing Algorithms
5. Hashing vs. Encryption
6. Hashing in Computer Science and Encryption
7. Using Hashing in Database Retrieval
8. Hashing's Role in File Tampering
9. Hashing Uses
10. Hashing in Cybersecurity
11. ?Hashing Pros & Cons
12. The Bottom Line
13. FAQs

How Hashing Works

Hashing uses algorithms that transform blocks of data from a file in a much shorter value or key of a fixed length that represents those strings. The resulting hash value is defined as a concentrated summary of every string within a given file and should be able to change even when a single byte of data in that file is changed (avalanche effect).

There are three main hashing components: the input data, the hash function or formula to convert the data, and the hash value.

This provides massive benefits in hashing in terms of data compression. While hashing is not compression, it can operate very much like file compression taking a larger data set and shrinking it into a more manageable form.

Suppose you had “John’s wallet ID” written 4000 times throughout a database. By taking all of those repetitive strings and hashing them into a shorter string, you’re saving tons of memory space.

Think of a three-word phrase encoded in a database or other memory location that can be hashed into a short alphanumeric value composed of only a few letters and numbers. This can be highly efficient at scale, and that’s just one reason that hashing is being used.

Types of Hashing Algorithms

There are several different types of hash algorithms, including RipeMD, Tiger, Whirlpool, xxhash, and more. The most common types used for file integrity checks are cryptographic hashes MD5, SHA-2, and CRC32.

MD5

An MD5 hash function encodes a string of any data of any length into a 128-bit fingerprint. MD5 hashes are often used to store small strings of sensitive data including passwords or credit card numbers in databases such as MySQL.

MD5 hashes are also used as a checksum to verify the data integrity of files. However, MD5 has security vulnerabilities as there is a high potential for hash collisions, which occur when two different pieces of information have the same generated hash value, and the shorter hash is easier to compromise in brute force attacks.

SHA-2

A secure hash algorithm (SHA) is a set of cryptographic hash functions developed by the U.S. National Security Agency (NSA). SHA-2 is an upgrade from its predecessor, SHA-1. SHA-2 comprises six hash functions:

• SHA-224
• SHA-256
• SHA-384
• SHA-512
• SHA-512/224
• SHA-512/256

Despite the different hash lengths, they are all based on the same underlying algorithm. SHA-2 algorithms are preferred over MD5, and SHA-256 is commonly used.

CRC32

A cyclic redundancy check (CRC) is an error-detecting code, which is often used to detect accidental changes to data.

It can check on any data block size and return a unique fixed-length checksum, with few collisions. The hash value obtained from the algorithm can be used to validate whether data has been changed, corrupted, or unintentionally damaged during transmission or storage by comparing it with the expected hash value.

Today, CRC32 is most often used for ZIP files and FTP servers.

Hashing vs. Encryption

Hashing is similar to encryption, but the two are used for different purposes. What is the difference between hashing and encryption?

Hashing is an efficient way to compare large amounts of data. It can also be used to map data as it is quick to find values, and it can be used in digital signatures and to create random strings to avoid the duplication of data stored in databases.

In contrast, encryption is typically used to encrypt data that is transmitted so that it cannot be read by anyone other than the intended recipient – even if an attacker intercepts the traffic, they cannot decipher the information. Encryption is also used to hide data stored in databases and authentication methods that can be retrieved when needed using a decryption key.

Hashing in Computer Science and Encryption

What is the purpose of hashing? Hashing has several key uses in computer science. Because hashed strings and inputs are not in their original form, they can’t be stolen the way they could be if they are not hashed.

If a hacker reaches into a database and finds an original string like “John’s wallet ID 34567,” they can simply glean, nab or pilfer this information and use it to their advantage, but if they instead find a hash value like “a67b2,” that information is completely useless to them, unless they have a key to decipher it.

A good hash function for security purposes must be a unidirectional process that uses a one-way hashing algorithm. Otherwise, hackers could easily reverse engineer the hash to convert it back to the original data, defeating the purpose of the encryption in the first place.

To further increase the uniqueness of encrypted outputs, random data could be added to the input of a hash function. This technique is known as “salting” and guarantees unique output even in the case of identical inputs. For example, hackers can guess users’ passwords in a database using a rainbow table or access them using a dictionary attack. Some users may share the same password that, if guessed by the hacker, is stolen for all of them. Adding the salt prevents the hacker from accessing these non-unique passwords, as each hash value will now be unique and will stop any rainbow table attack.

Using Hashing in Database Retrieval

Hashing can be used in database retrieval. Here’s where another example comes in handy – many experts analogize hashing to a key library innovation of the 20th century – the Dewey decimal system.

In a sense, retrieving a hash value can be explained as getting a Dewey decimal system number for a book. Instead of searching for the book’s title, you’re searching for the Dewey decimal system address or identification, plus a few key alphanumeric characters of the book’s title or author.

We’ve seen how well the Dewey decimal system works in libraries and just as well in computer science. In short, by shrinking these original input strings and data assets into short alphanumeric hash keys, engineers can do several key cybersecurity enhancements and save file space at the same time.

Hashing’s Role in File Tampering

Hashing is popular for database handling because of its effectiveness in preventing or identifying file tampering.

The original file generates a hash value stored with the file data. When the file is retrieved or transmitted, it is sent with the hash so that the recipient can check whether it has been changed or compromised.

Hashing Uses

Hashing has several useful applications, which make it one of the most commonly used data structures:

Hashing in Cybersecurity

Hash values provide a fast and effective form of threat detection. The ability to convert sensitive data into indecipherable values using hashing algorithms makes it an important cybersecurity tool for businesses and other organizations.

This is especially the case with the rise in remote work and the use of personal devices to connect to corporate networks, as there are more touchpoints for attackers to exploit, and users may not follow company best practices for keeping data secure.

Storing passwords as plain text is highly risky, but organizations can use a hashing tool to encode and save login credentials as hashed values for identity and access management (IAM) tools. In this way, password hashing helps prevent password-based cyberattacks.

Hashing files, documents, or datasets creates new hash values that organizations can use to track and identify compromised assets and quarantine them immediately. It can also prevent users from downloading malware.

Hashed values help ensure data security, as it is difficult for cybercriminals and malicious actors to decode them. So even if sensitive data is breached, it is in an unusable format. When used in digital signatures, hashing can authenticate the contents of a message as well as the sender’s identity.

However, it is important to be aware that cyberattacks can compromise hashes, such as a rainbow table attack, which uses a table of precomputed tables to crack the password hashes stored in a database. Such attacks mean it is essential to avoid relying on hashing alone and implement other forms of cybersecurity, such as antivirus software, to protect sensitive data.

?Hashing Pros & Cons

The Bottom Line

The definition of hashing is a form of algorithm used to convert data into fixed-size values for tasks including data retrieval, security, and data integrity. The benefits of hashing include fast access, compact storage, and enhanced security.

However, it is also important to be aware of limitations like the risk of collisions and irreversibility. Understanding the strengths and weaknesses of hashing is key to using it effectively for data indexing, password storage, digital signatures, and other applications.

FAQs