C++ is a powerful programming language that provides developers with the ability to write efficient and performant code. One of the key principles of C++ is “zero-cost abstractions” which allows programmers to use high-level abstractions without incurring any runtime overhead. In this blog post, we will explore how this principle can be applied to eliminate unnecessary data decryption in C++.

Understanding Zero-cost abstractions

Zero-cost abstractions in C++ means that high-level language features, such as classes, templates, and lambdas, should have no runtime performance impact compared to hand-written low-level code. This allows developers to write expressive and maintainable code without sacrificing performance.

Eliminating unnecessary data decryption

When working with encrypted data, it is common to decrypt the data before performing any operations on it. However, in certain scenarios, it is possible to eliminate the need for data decryption altogether, reducing both CPU and memory usage.

One approach to achieve this is by performing operations directly on the encrypted data by using homomorphic encryption techniques. Homomorphic encryption allows computations to be performed on encrypted data without first decrypting it. This not only eliminates the overhead of data decryption but also ensures the privacy of sensitive information.

Another approach is to use encrypted search algorithms, such as secure multi-party computation (MPC). With MPC, multiple parties can jointly compute the result of a search operation on their encrypted data without revealing the underlying data to each other. This allows for secure and privacy-preserving computations on encrypted data, eliminating the need for decryption.

Code example

#include <iostream>
#include <seal/seal.h>

int main()
{
    // Example code for using homomorphic encryption
    // Setup SEAL library context and keys
    seal::EncryptionParameters params(seal::scheme_type::bfv);
    // Initialize the parameters with appropriate values

    seal::KeyGenerator key_gen(params);
    seal::PublicKey public_key = key_gen.public_key();
    seal::SecretKey secret_key = key_gen.secret_key();
    seal::RelinKeys relin_keys = key_gen.relin_keys();

    seal::Encryptor encryptor(params, public_key);
    seal::Decryptor decryptor(params, secret_key);
    seal::Evaluator evaluator(params, relin_keys);

    // Encrypt some data
    seal::Plaintext data("42");
    seal::Ciphertext encrypted_data;
    encryptor.encrypt(data, encrypted_data);

    // Perform computations on encrypted data
    seal::Ciphertext encrypted_result;
    evaluator.square(encrypted_data, encrypted_result);
    evaluator.relinearize_inplace(encrypted_result, relin_keys);
    evaluator.rescale_to_next_inplace(encrypted_result);

    // Decrypt the result
    seal::Plaintext decrypted_result;
    decryptor.decrypt(encrypted_result, decrypted_result);

    std::cout << "Decrypted result: " << decrypted_result.to_string() << std::endl;

    return 0;
}

In the code example above, we demonstrate the use of the Microsoft SEAL library to perform computations on encrypted data using the Brakerski-Fan-Vercauteren (BFV) homomorphic encryption scheme. The code shows how data can be encrypted, computations can be performed on the encrypted data, and the result can be decrypted without ever decrypting the original data.

Conclusion

Zero-cost abstractions in C++ enable developers to write code that is both expressive and efficient. By leveraging homomorphic encryption and encrypted search algorithms, unnecessary data decryption can be eliminated, leading to improved performance and enhanced data privacy. C++ provides the tools necessary to implement these techniques and build secure and efficient applications.

Tags: #C++ #encryption