🧐 What is Homomorphic Encryption?

Homomorphic Encryption (HE) is a revolutionary cryptographic technique that allows computations to be performed on encrypted data without decrypting it. The result, when decrypted, matches the outcome of operations performed on the original plaintext data.

🔹 Why is Homomorphic Encryption Important?

✔ Ensures Data Privacy – No need to expose plaintext data for processing.
✔ Secure Cloud Computation – Allows outsourced computations on encrypted data.
✔ Prevents Data Leaks – Ideal for sensitive data like healthcare & finance.

🔑 How Homomorphic Encryption Works

Unlike traditional encryption, where data must be decrypted before processing, HE enables direct computation on encrypted data.

graph TD;
    User[🧑‍💻 User Encrypts Data] -->|Sends Encrypted Data 🔐| Server[🌐 Cloud Server]
    Server -->|Performs Computations 🔢| ProcessedData[🔄 Encrypted Computed Result]
    ProcessedData -->|Returns Encrypted Result 📩| User
    User -->|Decrypts with Private Key 🔑| FinalResult[✅ Correct Computation]

    style User fill:#c2f0c2,stroke:#333,stroke-width:2px
    style Server fill:#f9c2c2,stroke:#333,stroke-width:2px
    style ProcessedData fill:#87cefa,stroke:#333,stroke-width:2px
    style FinalResult fill:#fdfd96,stroke:#333,stroke-width:2px

📌 Key Steps in Homomorphic Encryption

✔ User encrypts the data before sending it to a cloud or third-party service.
✔ Server performs computations on the encrypted data without decryption.
✔ User decrypts the result after receiving the processed encrypted output.

🔹 Types of Homomorphic Encryption

📌 FHE is the ultimate goal, but it’s computationally expensive.

🛠️ Implementing Homomorphic Encryption in Node.js

Want to see Homomorphic Encryption in action? Here’s an example using the Paillier cryptosystem, a Partially Homomorphic Encryption (PHE) method that supports addition on encrypted values.

📌 Step 1: Install a Homomorphic Encryption Library

npm install node-paillier

📌 Step 2: Generate Key Pair for Encryption

const paillier = require('node-paillier');

// Generate Public & Private Keys
const { publicKey, privateKey } = paillier.generateRandomKeys(2048);
console.log("🔑 Public Key:", publicKey);
console.log("🔐 Private Key:", privateKey);

📌 Step 3: Encrypt Two Numbers & Perform Addition on Encrypted Data

// Encrypt two numbers
const num1 = 15;
const num2 = 10;
const encryptedNum1 = publicKey.encrypt(num1);
const encryptedNum2 = publicKey.encrypt(num2);

console.log("🔐 Encrypted Number 1:", encryptedNum1.toString());
console.log("🔐 Encrypted Number 2:", encryptedNum2.toString());

// Perform Addition on Encrypted Data
const encryptedSum = publicKey.addition(encryptedNum1, encryptedNum2);
console.log("➕ Encrypted Sum:", encryptedSum.toString());

📌 Step 4: Decrypt the Computed Result

// Decrypt the computed sum
const decryptedSum = privateKey.decrypt(encryptedSum);
console.log("✅ Decrypted Sum:", decryptedSum); // Output: 25

🚀 Final Thoughts

Homomorphic Encryption enables secure computation on encrypted data, opening the door for privacy-preserving AI, secure cloud computing, and confidential financial operations.

✅ Use PHE for simple operations like authentication.
✅ SHE is great for structured AI and analytics models.
✅ FHE is the future but still requires performance optimizations.

Would you like a deep dive into Fully Homomorphic Encryption (FHE) and its real-world applications? Let’s discuss in the comments! 👇

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About Me 👨‍💻

I'm Faiz A. Farooqui. Software Engineer from Bengaluru, India.
Find out more about me @ faizahmed.in