> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mindgard.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Homomorphic Encryption

> Encrypt data into a form the model can process

export const what_0 = "This protects the privacy of each individual input but introduces computational performance overhead."

export const how_0 = "Prevents attacker from acquiring readable data from the model."

export const implement_0 = "Homomorphic encryption methods during training."

Encrypts data in a form that a neural network can process without data decryption. This protects the privacy of each individual input but introduces computational performance overhead and limits the set of arithmetic operations to those supported by Homomorphic Encryption.

## Explanation

{what_0} 

## How it works

{how_0} 

## How to implement

{implement_0}