Design and Development of Quantum and ML-Based Cryptography System for SoC Applications

Abstract

In recent decades, quantum computing-based cryptography has become the latest and more secure for sending of data through different protocols that could be wired or wireless in communications. To optimize power dynamic and static utilization in digital circuits, Machine Learning (ML) and Quantum computing are playing a major role in designing and implementing cryptography systems. The combination of these two techniques will increase the security level and be used for key authentications and integrity. Quantum Key Distribution (QKD) along with ML enables the communicating parties to detect the side channel effects and protection of keys from noisy channels. To guarantee two parties have access to significant sections of the key, the QKD creates random keys for private and public data transmission. The SHA-256 generates 256-bit hash values that are used for authenticating the signatures and data on the fly so that encryption and decryption can process their operation without waiting for hash values as private and public keys. The proposed design has been validated using benchmarking the overhead and measured performance degradation and shown their suitability for SoC and FPGA systems.