A Framework for Strengthening Quantum Cryptography with Machine Learning and Error Correction

Abstract

The rapid development of quantum computing poses a significant threat to classical cryptographic systems that rely on computational hardness assumptions. In order to tackle this difficulty, this paper suggests a hybrid quantum-inspired secure communication system which merges Quantum Key Distribution (QKD) based on the BB84 protocol and classical encryption, steganography and blockchain-based auditing. The suggested system facilitates safe transmission of all data modalities such as text, images, audio and video. To monitor quantum Bit Error Rate (QBER) to identify attempts of eavesdropping and simulate the adversarial interference, the system is trained on a GAN-like attack model. The system also enforces two-factor authentication over Time-based One-Time Passwords (TOTP) and the logs are stored in an immutable blockchain system through a minimal blockchain implementation. Security analytics dashboard monitor is a real-time operation that overviews the security measurements of the system. As in experimental findings, the framework proposed proves to be practical, scale-able and quantum resilient and befitting the contemporary secure communication set-up.