#What is Fully Homomorphic Encryption?
Fully homomorphic encryption (FHE) is a form of encryption that allows data to be processed without ever being decrypted. It enables computations on encrypted data, while still preserving its confidentiality. FHE works by using homomorphic algorithms that enable the calculation of an encrypted value and then re-encrypting it with another key, so that neither the original nor the final result are readable in plaintext. This type of encryption has been used for a number of applications such as secure database storage, cloud computing, and even machine learning algorithms.
#How Does Fully Homomorphic Encryption Work?
FHE works by encrypting data before it’s stored or sent over the internet. The encryption process uses a combination of two keys – one public key which everyone can access and one private key which only you have access to. When data is sent from point A to point B it’s encrypted with both these keys so that only those who possess both can read or modify it in any way. Then when someone wants to use this data they must decrypt it using their own private key while encrypting with your public key at the same time – meaning no one else can see what operations were performed on your data during processing except for you and whoever was authorized by you (the sender).
The actual calculations themselves are done using either fully homomorphic algorithms (which work directly on ciphertext) or partially homomorphic ones (which require plaintext inputs). These algorithms allow programs written in languages like Java or C++ to run without having any knowledge about how they were originally encrypted – making them ideal for tasks such as securely storing confidential information online or ensuring privacy protection when running analytics software remotely.
#Benefits Of Fully Homomorphic Encryption
The main benefit of FHE is its ability to provide security and privacy for sensitive information even after processing has taken place; this means there’s no need for anyone other than those who created/own the information to know anything about what happened during calculations involving said information – perfect if you want keep confidential details hidden away! Additionally, since FHE eliminates any need for additional infrastructure setup prior to use (such as setting up multiple computers dedicated solely towards running certain tasks), overall costs associated with deploying systems based around this technology tend be much lower compared conventional approaches – making them particularly attractive options within organizations already dealing large volumes sensitive records daily basis . Finally, because all computation happens locally rather than over an external network connection there’s also significantly less latency involved – resulting better performance times too!
