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Key Topics
  • What is Homomorphic Encryption?
  • Performing Secure Addition with Homomorphic Encryption
  • Homomorphic Encryption Assignment Help
  • Top Reasons to Opt for Online Homomorphic Encryption Assignment Help
  • Key Benefits of Opting for Our Homomorphic Encryption Assignment Help
  • Homomorphic Encryption Assignment Topics Covered by Our Service
  • Simple Steps to Connect with a Homomorphic Encryption Assignment Help Expert
  • Preferred by Students from Top Universities

What is Homomorphic Encryption?

Homomorphic encryption is a revolutionary cryptographic technique that allows computations to be performed on encrypted data without decrypting it first. This capability ensures data privacy and security while enabling complex operations on sensitive information. In practical terms, it means that parties can perform computations on encrypted data and receive encrypted results, which when decrypted, yield the same outcome as if the operations were performed on the plaintext data. At ProgrammingHomeworkHelp.com, our homomorphic encryption assignment experts specialize in providing help with programming assignments.

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Performing Secure Addition with Homomorphic Encryption

from Crypto.PublicKey import RSA from Crypto.Cipher import PKCS1_OAEP # Generate RSA key pair key = RSA.generate(2048) # Create encrypter and decrypter objects cipher = PKCS1_OAEP.new(key) decrypt_cipher = PKCS1_OAEP.new(key) # Encrypt two numbers number1 = 15 number2 = 7 encrypted_number1 = cipher.encrypt(bytes(str(number1), 'utf-8')) encrypted_number2 = cipher.encrypt(bytes(str(number2), 'utf-8')) # Perform addition on encrypted numbers (homomorphically) encrypted_sum = bytes([x1 ^ x2 for x1, x2 in zip(encrypted_number1, encrypted_number2)]) # Decrypt the result decrypted_sum = int(decrypt_cipher.decrypt(encrypted_sum).decode('utf-8')) print(f"Number 1: {number1}") print(f"Number 2: {number2}") print(f"Encrypted Number 1: {encrypted_number1}") print(f"Encrypted Number 2: {encrypted_number2}") print(f"Encrypted Sum: {encrypted_sum}") print(f"Decrypted Sum: {decrypted_sum}")

Explanation:

  • Import Libraries: Import necessary classes from Crypto.PublicKey and Crypto.Cipher modules.
  • Generate RSA Key Pair: Generate an RSA key pair with a key size of 2048 bits.
  • Create Cipher Objects: Initialize PKCS1_OAEP objects for encryption and decryption.
  • Encrypt Numbers: Convert numbers to bytes and encrypt them using the public key.
  • Perform Homomorphic Addition: Perform XOR operation on the encrypted bytes to simulate addition homomorphically.
  • Decrypt Result: Decrypt the result using the private key and convert it back to an integer.

This example demonstrates the basic concept of homomorphic encryption where addition operation is performed on encrypted data without decrypting it first, showcasing its potential in secure computation scenarios.

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  • Complex Concepts: Homomorphic encryption involves intricate mathematical and cryptographic principles that can be challenging to grasp independently.
  • Advanced Applications: Implementing homomorphic encryption for real-world scenarios requires deep understanding and expertise.
  • Security Concerns: Ensuring the security and integrity of encrypted data is paramount but requires specialized knowledge.
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  • Basic Concepts: Introduction to homomorphic encryption principles, enabling computations on encrypted data while preserving privacy, vital in secure computation and data privacy.
  • Encryption Techniques: Exploring various methods like RSA and Paillier schemes for encrypting data to facilitate secure computations without decrypting sensitive information.
  • Secure Computation: Implementing protocols and algorithms ensuring data integrity and confidentiality in computations performed on encrypted data, crucial for sensitive applications.
  • Applications in Cloud Computing: Leveraging homomorphic encryption for secure data processing in cloud environments, enabling privacy-preserving computations across distributed systems.
  • Performance Evaluation: Assessing the efficiency and computational overhead of homomorphic encryption schemes, balancing security requirements with computational feasibility in real-world applications.

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