Hashing Types: The 3 Encryption Techniques to Know (2023)

Hashing Types

Imagine that you’re a librarian and you have an enormous number of books to manage. The books are different shapes, sizes, and topics, and they’re all over the place! A good librarian, you’d want a way to categorize these books so you can quickly find the right one when needed. This, in a nutshell, is what computer hashing does. But instead of books, it deals with data. Are you ready to discover how it’s done?

Summary

Hashing is a computational process that converts any size of data into a unique fixed length string, like an address, making it easier and faster to retrieve the original data when needed.

Type 1 – Cryptographic Hash Functions: This type of hashing is at the heart of blockchain technology and cryptocurrencies like Bitcoin. It’s fascinating because it’s designed to be secure, meaning the data hashed cannot be reversed or decrypted, which is critical for online security and privacy.

Type 2 – Consistent Hashing: This is a special kind of hashing used in distributing data across multiple servers, commonly seen in large-scale Internet companies. Its magic lies in its ability to add or remove servers with minimal data reorganization, reducing the risk of data loss and ensuring high availability.

Type 3 – Locality-Sensitive Hashing (LSH): LSH is used when dealing with high-dimensional data, like images or genetic data. It’s interesting because it can identify items that are similar and group them together, making it a key technique in recommendation systems and image or voice recognition.

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Hashing Types In-depth

Cryptographic Hash Functions

Have you ever wondered how your sensitive information like passwords remain secure when you use them online? How does a system know it’s you without actually ‘seeing’ your password? You can thank Cryptographic Hash Functions for that. Let’s unpack this a bit.

Imagine you’re sending a secret message to a friend, but you don’t want anyone else to read it. What do you do? Well, you might develop a secret code that only you and your friend understand. Cryptographic Hash Functions work in a similar way, but instead of a simple secret code, they use complex mathematical operations to transform your message (or in computer terms, your ‘input data’) into a jumble of numbers and letters, known as a ‘hash’. The special thing here is that this transformation is one-way. Once your message is turned into a hash, there’s no easy way to turn it back.

So, how does this come into play when you’re logging into your email, for instance? When you first create your password, the system uses a Cryptographic Hash Function to transform it into a hash, and then stores that hash. The next time you log in, the system transforms the password you enter into a hash in the same way and checks if it matches the stored hash. If it does, voila, you’re in! At no point does the system actually ‘see’ or ‘store’ your real password. Cool, right?

But there’s even more! Cryptographic Hash Functions are designed so that even a tiny change in the input data (like changing a single letter in your password) will produce a dramatically different hash. This means that if someone tries to guess your password, they can’t get any clues from the hash, because every guess will produce a completely different hash. This is the brilliance of Cryptographic Hash Functions.

They are also deterministic, which means that any given input data will always produce the same hash. This consistent output, no matter how many times the same input is hashed, ensures that data integrity is maintained.

Cryptographic Hash Functions form the backbone of secure communication on the internet, from protecting our passwords to creating digital signatures for verifying document authenticity. They’re like the invisible superheroes keeping our data safe from prying eyes, one hash at a time.

In the next section, we’ll dive into another fascinating type of hashing – Consistent Hashing. Are you ready to continue the adventure?

Consistent Hashing

Imagine you’re playing a game of musical chairs. The music starts, and everyone begins circling a set of chairs. When the music stops, everyone scrambles for a seat. Now, imagine if you could design a game where, even when a chair is added or removed, everyone knows exactly where to sit. This is the concept behind Consistent Hashing.

In the digital realm, instead of people and chairs, we have data and servers. Traditional hashing methods can lead to a lot of chaos (or in technical terms, ‘rehashing’) when a server is added or removed, as they would change the place where every piece of data should go. This is like adding or removing a chair in musical chairs and seeing everyone scramble! But with Consistent Hashing, the impact of a change is minimized.

Think of Consistent Hashing like a circular track with various stops. Each stop represents a server, and each passenger (data) has a specific destination (hash). When a new server (stop) is added or an old one is removed, it doesn’t create a major reshuffle of passengers. The passengers close to that stop might move, but the others stay put.

Consistent Hashing is extremely important for businesses that need to manage large amounts of data across multiple servers, like internet giants Google or Facebook. It helps them ensure that their service continues to run smoothly even when servers are added or removed. This means less downtime and better service for users. Moreover, it also helps distribute data evenly across servers, preventing some servers from being overloaded while others sit idle.

At its core, Consistent Hashing is a clever way of turning the chaos of a musical chairs game into an orderly, smooth process. It’s like a traffic cop for the digital world, keeping data flowing smoothly along the information highway.

In our next stop on this hashing journey, we’ll discover the wonders of Locality-Sensitive Hashing. Ready for more?

Locality-Sensitive Hashing (LSH)

Remember the last time you tried to sort a pile of mixed socks? The first thing you probably did was to put similar socks together. Stripes with stripes, polka dots with polka dots, right? This is essentially what Locality-Sensitive Hashing does, but with data!

In the digital world, we often deal with high-dimensional data. Imagine data as a room full of people. Each person has many attributes, such as hair color, height, eye color, shoe size – these attributes represent dimensions. Now, if you’re looking for someone who matches a certain set of attributes, you’d need to go around asking each person. This could take a long time!

But what if there was a way to group similar people together, so you only need to look in one small group instead of the entire room? This is where Locality-Sensitive Hashing shines. LSH has a special trick: it hashes similar items to the same or nearby buckets. In other words, it puts similar socks (or in this case, data points) together!

You can see why this is handy, right? For example, let’s say you run a music streaming service and want to recommend songs to a user. With LSH, you can quickly find songs that are similar to the ones the user already likes, without having to compare every single song in your database.

Or, consider an image search engine. If a user searches for a picture of a golden retriever, LSH helps the search engine quickly find similar images by only checking in the ‘golden retriever’ bucket, rather than sifting through millions of unrelated images.

In essence, Locality-Sensitive Hashing is like a super-efficient sorting system. It might not be able to find the exact pair for a sock, but it’ll definitely get you to the right drawer faster. And in the vast and complex world of data, that’s a win!

That concludes our adventure through the intriguing land of hashing. From the secure encryption of Cryptographic Hash Functions, the minimal reorganization of Consistent Hashing, to the quick similarity search in Locality-Sensitive Hashing, it’s been quite a journey, hasn’t it?

Conclusions

In conclusion, the world of hashing is both vast and captivating. Just like a universal translator helping us understand different languages, hashing helps our computers manage and retrieve data efficiently. From safeguarding our digital lives with Cryptographic Hash Functions, streamlining data traffic with Consistent Hashing, to smartly organizing complex data using Locality-Sensitive Hashing, hashing truly is the unsung hero in the digital realm.

As we step into a future of increasing digitalization, the role of hashing becomes ever more crucial. The next time you log into a website or search for a song, remember, there’s a world of hashing magic happening behind the scenes.

How to stay safe online:

• Practice Strong Password Hygiene: Use a unique and complex password for each account. A password manager can help generate and store them. In addition, enable two-factor authentication (2FA) whenever available.
• Invest in Your Safety: Buying the best antivirus for Windows 11 is key for your online security. A high-quality antivirus like Norton, McAfee, or Bitdefender will safeguard your PC from various online threats, including malware, ransomware, and spyware.
• Be Wary of Phishing Attempts: Be cautious when receiving suspicious communications that ask for personal information. Legitimate businesses will never ask for sensitive details via email or text. Before clicking on any links, ensure the sender's authenticity.
• Stay Informed. We cover a wide range of cybersecurity topics on our blog. And there are several credible sources offering threat reports and recommendations, such as NIST, CISA, FBI, ENISA, Symantec, Verizon, Cisco, Crowdstrike, and many more.

Happy surfing!

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