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Documentation Index

Fetch the complete documentation index at: https://docs.privora.xyz/llms.txt

Use this file to discover all available pages before exploring further.

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Understanding Fully Homomorphic Encryption

Fully Homomorphic Encryption (FHE) allows computations on encrypted data without decrypting it. This page explains the fundamentals and how Privora uses FHE.

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What is Homomorphic Encryption?

Homomorphic encryption is a form of encryption that allows specific mathematical operations to be performed on ciphertexts, producing an encrypted result that, when decrypted, matches the result of operations performed on the plaintext. 
Encrypt(A) + Encrypt(B) = Encrypt(A + B)
This means programs can process sensitive data without ever seeing the actual values.

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TFHE (Torus FHE)

Privora uses TFHE (Torus Fully Homomorphic Encryption), a modern FHE scheme with:
  • Fast Boolean and Integer Operations: Efficient arithmetic on encrypted integers
  • Programmable Bootstrapping: Enables arbitrary operations through function evaluation
  • Practical Performance: Fast enough for real-world applications

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Supported Operations

Privora supports the following operations on encrypted data:

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Arithmetic Operations

OperationMethodOperatorExample
Addition.add(&other)&a + &blet sum = a.add(&b)?;
Subtraction.sub(&other)&a - &blet diff = a.sub(&b)?;
Multiplication.mul(&other)&a * &blet prod = a.mul(&b)?;
use privora_sdk_program::prelude::*;

// Load encrypted values
let a: Encrypted<u64> = a_ref.load()?;
let b: Encrypted<u64> = b_ref.load()?;

// Using methods (returns Result)
let sum = a.add(&b)?;
let difference = a.sub(&b)?;
let product = a.mul(&b)?;

// Using operators (panics on error)
let sum = &a + &b;
let difference = &a - &b;
let product = &a * &b;

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Comparison Operations

OperationMethodReturns
Greater or Equal.ge(&other)EncryptedBool
Greater Than.gt(&other)EncryptedBool
Less or Equal.le(&other)EncryptedBool
Less Than.lt(&other)EncryptedBool
Equal.eq_enc(&other)EncryptedBool
// Compare encrypted values
let is_greater: EncryptedBool = price.ge(&threshold)?;
let is_equal: EncryptedBool = value_a.eq_enc(&value_b)?;
Comparison operations are more expensive than arithmetic operations in FHE. See the optimization guide for best practices.

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Min/Max Operations

// Get minimum/maximum of two encrypted values
let minimum = buy_qty.min(&sell_qty)?;
let maximum = price_a.max(&price_b)?;

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Conditional Selection

The select operation is the FHE equivalent of an if-then-else: 
// If condition is true, return true_val; otherwise return false_val
let result = condition.select(&true_val, &false_val)?;
This is essential for implementing branching logic in FHE programs: 
// Example: Select price based on match condition
let can_match: EncryptedBool = buy_price.ge(&sell_price)?;
let fill_price = can_match.select(&sell_price, &buy_price)?;
// Equivalent to: if (buy >= sell) { sell_price } else { buy_price }

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Supported Integer Types

TypeRust TypeRangeCiphertext Size
u8Encrypted<u8>0-255~10KB
u32Encrypted<u32>0-4B~40KB
u64Encrypted<u64>0-18Q~80KB
Choose the smallest integer type that fits your use case. Larger types have proportionally larger ciphertexts and slower operations.

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Performance Characteristics

FHE operations have different performance profiles:
OperationRelative CostNotes
AdditionLowFast, use freely
SubtractionLowSame as addition
MultiplicationMedium~2-3x addition
ComparisonHighRequires bootstrapping
Min/MaxHighBuilt on comparison
SelectHighBuilt on comparison

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Optimization Tips

  1. Minimize comparisons: Each comparison is expensive; batch when possible
  2. Use smaller types: u8 operations are faster than u64
  3. Avoid deep chains: FHE operations add noise; keep computation chains short
  4. Batch operations: Submit multiple operations in a single transaction

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Ciphertext Properties

FHE ciphertexts have specific properties:
PropertyDescription
DeterministicSame plaintext + key = same ciphertext
Large10KB-100KB depending on type
NoiseOperations add noise; too much = decryption failure
Type-boundCannot mix Encrypted<u8> with Encrypted<u64>

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Security Considerations

  • 128-bit security: TFHE parameters provide ~128-bit security
  • Key management: FHE public key is shared; private key is distributed via MPC
  • No plaintext leakage: Programs never see plaintext during computation
  • Verifiable computation: All FHE operations are deterministic and verifiable

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Next Steps

Encrypted Types

Learn about the Privora type system

Program Development

Start building FHE programs