In this article we will be discussing of applications of hashing.
Hashing provides constant time search, insert and delete operations on average. This is why hashing is one of the most used data structure, example problems are, distinct elements, counting frequencies of items, finding duplicates, etc.
There are many other applications of hashing, including modern day cryptography hash functions. Some of these applications are listed below:
- Message Digest
- Password Verification
- Data Structures(Programming Languages)
- Compiler Operation
- Rabin-Karp Algortithm
- Linking File name and path together
This is an application of cryptographic Hash Functions. Cryptographic hash functions are the functions which produce an output from which reaching the input is close to impossible. This property of hash functions is called irreversibility.
Lets take an Example:
Suppose you have to store your files on any of the cloud services available. You have to be sure that the files that you store are not tampered by any third party. You do it by computing “hash” of that file using a Cryptographic hash algorithm. One of the common cryptographic hash algorithms is SHA 256. The hash thus computed has a maximum size of 32 bytes. So a computing the
hash of large number of files will not be a problem. You save these hashes on your local machine.
Now, when you download the files, you compute the hash again. Then you match it with the previous hash computed. Therefore, you know whether your files were tampered or not. If anybody tamper with the file, the hash value of the file will definitely change. Tampering the file without changing the hash is nearly impossible.
Cryptographic hash functions are very commonly used in password verification. Let’s understand this using an Example:
When you use any online website which requires a user login, you enter your E-mail and password to authenticate that the account you are trying to use belongs to you. When the password is entered, a hash of the password is computed which is then sent to the server for verification of the password. The passwords stored on the server are actually computed hash values of the original passwords. This is done to ensure that when the password is sent from client to server, no sniffing is there.
Data Structures(Programming Languages):
Various programming languages have hash table based Data Structures. The basic idea is to create a key-value pair where key is supposed to be a unique value, whereas value can be same for different keys. This implementation is seen in unordered_set & unordered_map in C++, HashSet & HashMap in java, dict in python etc.
The keywords of a programming language are processed differently than other identifiers. To differentiate between the keywords of a programming language(if, else, for, return etc.) and other identifiers and to successfully compile the program, the compiler stores all these keywords in a set which is implemented using a hash table.
One of the most famous applications of hashing is the Rabin-Karp algorithm. This is basically a string-searching algorithm which uses hashing to find any one set of patterns in a string. A practical application of this algorithm is detecting plagiarism. To know more about Rabin-Karp algo go through Searching for Patterns | Set 3 (Rabin-Karp Algorithm).
Linking File name and path together:
When moving through files on our local system, we observe two very crucial components of a file i.e. file_name and file_path. In order to store the correspondence between file_name and file_path the system uses a map(file_name, file_path)which is implemented using a hash table.
- Hashing in Java
- Coalesced hashing
- Double Hashing
- Hashing | Set 1 (Introduction)
- C++ program for hashing with chaining
- How to use bcrypt for hashing passwords in PHP?
- Hashing | Set 2 (Separate Chaining)
- Hashing | Set 3 (Open Addressing)
- Majority Element | Set-2 (Hashing)
- Practice Problems on Hashing
- GRE Algebra | Applications
- Address Calculation Sort using Hashing
- Deploying Node Applications
- Rearrange characters in a string such that no two adjacent are same using hashing
- Union and Intersection of two linked lists | Set-3 (Hashing)
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.