Quantum cryptography in Convolution neural network approach in Smart cities

Abstract

Quantum cryptography is a field that has achieved  ample of attraction in lately to the increasing need for secure communication in various applications. Smart cities are one such application where secure communication is crucial for ensuring the safety and privacy of citizens. In this context, this paper proposes a novel approach to secure communication in smart cities using quantum cryptography and convolution neural networks (CNN). The proposed approach involves the use of quantum key distribution (QKD) for secure key exchange between the communicating parties. The key obtained through QKD is then used to encrypt the data using a convolutional neural network. The CNN-based encryption provides an additional layer of security to the data transmitted in smart cities. The evaluation  of the proposed approach is assessed through simulations and the outcomes demonstrate that the CNN-based encryption significantly improves the security of the communication compared to traditional encryption methods. Furthermore, the approach is shown to be efficient and scalable for use in large-scale smart city applications. Overall, the proposed approach presents a promising solution for secure communication in smart cities using quantum cryptography and convolution neural networks. The approach can be further developed and optimized to meet the specific security and performance requirements of different smart city applications.