Understanding Fully Homomorphic Encryption: Use Cases & C Examples

4 min read

Understanding Fully Homomorphic Encryption: Use Cases & C Examples

Ever wish you could run computations on encrypted data without ever decrypting it? Like, imagine sending your secrets to a cloud server, and it crunches the numbers without ever peeking inside. Sounds like sci-fi? Welcome to the wizardry of Fully Homomorphic Encryption (FHE) — the cryptographic holy grail that’s been the holy grail for decades and is finally coming into practical reach.

What the Heck is Fully Homomorphic Encryption?

At its core, FHE lets you perform arbitrary computations on ciphertexts as if you were working with plaintexts. The result? An encrypted output that, when decrypted, matches the result of the operation as if it was done on the original data. No need to trust the party doing the computation—they never see your raw data. This flips traditional encryption on its head, where you usually have to decrypt before processing.

The MMU of Crypto: Why FHE is a Game-Changer

Think of FHE as the CPU’s memory management unit (MMU) for data privacy. Just like the MMU translates virtual addresses to physical memory without the CPU needing to know the physical layout, FHE translates operations on ciphertexts into meaningful results on plaintexts—without exposing the data. It’s like giving the cloud a blindfold but still letting it juggle your secrets perfectly.

Real-World Use Cases That Make You Go 🤯

  • Privacy-Preserving Machine Learning: Train or query ML models on encrypted data without leaking sensitive info. Hospitals can share patient data insights without exposing records.
  • Secure Cloud Computing: Outsource computations to the cloud while keeping your data locked down tight.
  • Encrypted Databases: Query encrypted databases directly, no decrypting required.
  • Voting Systems: Count votes encrypted end-to-end, ensuring both privacy and verifiability.
  • Financial Services: Perform risk analysis or fraud detection on encrypted financial data.

The Nitty-Gritty: How Does FHE Work Under the Hood?

FHE schemes typically rely on hard problems from lattice-based cryptography—think of these as complicated puzzles that are easy to create but insanely hard to solve without the secret key. The most popular constructions are based on the Learning With Errors (LWE) or Ring-LWE problems.

Here’s a high-level breakdown:

  1. Key Generation: Produces a public key for encryption and a secret key for decryption.
  2. Encryption: Turns plaintext into ciphertext with some noise added.
  3. Evaluation: Applies arithmetic operations (addition, multiplication) directly on ciphertexts.
  4. Decryption: Recovers the plaintext from the processed ciphertext.

The tricky part? Noise accumulates as you do more operations, threatening correctness. Modern schemes use clever bootstrapping techniques to “refresh” ciphertexts and keep noise in check.

Let’s Get Our Hands Dirty: A Simple C Example Using a Trusted FHE Library

Rolling your own FHE from scratch is a beast. Instead, we lean on battle-tested libraries like Microsoft SEAL or PALISADE. Today, we'll use Microsoft SEAL’s C API to demonstrate a tiny encrypted addition.

Setup: Grab Microsoft SEAL and Build the C API

Microsoft SEAL is primarily C++, but it provides a C wrapper. Assume you’ve built and linked against SEAL’s C API.

Code: Encrypt, Add, and Decrypt

#include <stdio.h>
#include <seal/c/c.h>

int main() {
    // Step 1: Create encryption parameters
    SEALContext *context = NULL;
    EncryptionParameters *params = EncryptionParameters_Create(seal_scheme_type_bfv);
    
    // Set poly_modulus_degree and coeff_modulus for BFV scheme
    EncryptionParameters_SetPolyModulusDegree(params, 2048);
    EncryptionParameters_SetCoeffModulusBFVDefault(params, 2048);
    EncryptionParameters_SetPlainModulus(params, 256);

    // Create context
    context = SEALContext_Create(params, true, sec_level_type_tc128);

    // Keys
    KeyGenerator *keygen = KeyGenerator_Create(context);
    PublicKey *public_key = KeyGenerator_PublicKey(keygen);
    SecretKey *secret_key = KeyGenerator_SecretKey(keygen);

    // Encryptor, decryptor, evaluator
    Encryptor *encryptor = Encryptor_Create(context, public_key);
    Decryptor *decryptor = Decryptor_Create(context, secret_key);
    Evaluator *evaluator = Evaluator_Create(context);

    // Plaintexts
    Plaintext *plain1 = Plaintext_Create();
    Plaintext *plain2 = Plaintext_Create();
    Plaintext_Set(plain1, "6");
    Plaintext_Set(plain2, "7");

    // Encrypt plaintexts
    Ciphertext *cipher1 = Ciphertext_Create();
    Ciphertext *cipher2 = Ciphertext_Create();
    Encryptor_EncryptPlain(encryptor, plain1, cipher1);
    Encryptor_EncryptPlain(encryptor, plain2, cipher2);

    // Add ciphertexts
    Ciphertext *result = Ciphertext_Create();
    Evaluator_Add(evaluator, cipher1, cipher2, result);

    // Decrypt result
    Plaintext *plain_result = Plaintext_Create();
    Decryptor_Decrypt(decryptor, result, plain_result);

    // Print result
    printf("Decrypted result: %s\n", Plaintext_ToString(plain_result));

    // Cleanup
    Plaintext_Destroy(plain1);
    Plaintext_Destroy(plain2);
    Plaintext_Destroy(plain_result);
    Ciphertext_Destroy(cipher1);
    Ciphertext_Destroy(cipher2);
    Ciphertext_Destroy(result);
    Encryptor_Destroy(encryptor);
    Decryptor_Destroy(decryptor);
    Evaluator_Destroy(evaluator);
    KeyGenerator_Destroy(keygen);
    PublicKey_Destroy(public_key);
    SecretKey_Destroy(secret_key);
    SEALContext_Destroy(context);
    EncryptionParameters_Destroy(params);

    return 0;
}

What’s Happening Here?

  • We set up BFV parameters—a popular FHE scheme for integer arithmetic.
  • Generate keys and create encryptor/decryptor/evaluator objects.
  • Encrypt two integers (6 and 7).
  • Add their ciphertexts directly.
  • Decrypt the result, which prints 13.

Simple, right? Under the hood, the library handles noise management and bootstrapping so you don’t have to.

TL;DR

  • FHE lets you compute on encrypted data without decrypting it.
  • It’s a massive leap for privacy-preserving computing and secure cloud services.
  • Built on lattice-based cryptography, FHE deals with noise and bootstrapping to keep ciphertexts valid.
  • Using libraries like Microsoft SEAL, you can do encrypted math in C with surprisingly little fuss.
  • The future is computation without compromise—your data stays locked tight, yet useful.

The Mic Drop

Fully Homomorphic Encryption isn’t just a cryptographer’s pipe dream anymore—it’s your next secret weapon for building systems where privacy and utility coexist. So, what encrypted computation are you going to build first? Drop your wildest ideas below. 🚀⚙️

Stay curious, stay encrypted.