Secure your data with Homomorphic Encryption

The demand for the privacy of digital data and algorithms for security has increased rapidly over the last decade. And also the growth in communication networks and their devices are increasing parallelly at the same time, these networks are subjected to a variety of attacks that includes the destruction of data and manipulation and theft of sensitive information. 

Currently, there are so many methods to save the privacy of stored data such as encryption of data and usage of tamper-resistant hardware, but the main problem occurs when there is a need for computing(publicly) with private data. In this situation, Homomorphic encryption is used. 


Homomorphic encryption is a type of encryption that allows users to perform computations on their encrypted data without decrypting it. Homomorphic encryption is used for privacy-preserving outsourced storage and computation. The data is encrypted and outsourced to a commercial cloud environment for processing. For example, health care analysis can be a risk to apply through a third-party service but if it is done through encrypted data instead,  then its privacy concerns are saved.


There are three types of homomorphic encryption. They differ from one another in the frequency of mathematical operations. Here are the three types of homomorphic encryption

  • Partially Homomorphic Encryptions
  • Somewhat Homomorphic Encryption
  • Fully Homomorphic Encryption.



In this method the mathematical functions are performed on encrypted values, which means only one operation is performed at a time, either multiplication or addition is performed in unlimited times on the ciphertext. Multiplication operation of Partial Homomorphic Encryption is the foundation for RSA encryption which is used for secure connection through SSL/TLS.


This method allows the selection operation of either multiplication or addition with some complexity and can be performed a set number of times.


Fully Homomorphic Encryption is the development stage that has many potentials for running functionality with privacy. It is responsible for information security which can also be accessed at the same time. FHE is capable of performing addition and multiplication at any number of times. Like another encryption type FHE can also handle arbitrary computations on ciphertexts.  It allows anyone to use encrypted data and perform required operations without access to the encryption key. Because of this, the security of cloud computing has improved. 



Search engines provide answers to the users, while doing so they also show ads to the user which is the main key to generate revenues, but this causes great effect for the users. Thus Homomorphic Encryption solves this problem, the search engines can crawl the encrypted data and serve the result but it cannot show ads.


Importantly,  databases should be protected from cyber-attacks. In this case, the database should be encrypted and decrypted by a specific key. The standard encryption does not allow any unwanted operations on the records. There are also many encryption methods such as order-revealing encryption, order-preserving encryption, and deterministic encryption but using this can lead to leakage of memory access patterns. To avoid this kind of problem the best solution is to use Homomorphic encryption.


Homomorphic Encryption is typically slow and can perform a limited number of operations. FHE-based computations are 100 times slower than normal computations. This is not effective when it comes to practical applications, if we need multiple users to access a database then we should create a separate database for every user which is difficult when the number of users increases.


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