Authors:
Sai Teja Kotagiri
Addresses:
Department of Cybersecurity, Caliber Tech LLC, Texas, United States of America.
Abstract:
This Quantum Cryptography, as a future generation cyber security protocol research, includes experimental data that have been gathered from publicly accessible quantum cryptographic experiments done by university research facilities and cyber security facilities. The data comprises performance records of Quantum Key Distribution (QKD) deployments across various network environments and networks. Critical parameters, including encryption success rates, error rates, latency, throughput, and QKD efficiency, were studied to ensure the security and reliability of quantum cryptographic protocols being implemented. Experimental setups, such as Qiskit and QuTech, are utilized in experiments that offer the functionality to simulate and test quantum cryptographic systems. Quantum circuit building, quantum protocol simulation, and performance monitoring against various network topologies are facilitated by these platforms. Moreover, the experimental setup utilized actual quantum key distribution hardware and secure communication channels to facilitate real-time experimentation. Visualization employed Matplotlib to produce histograms and 3D plots of the success rates, throughput, and latency. Statistical modeling was performed to estimate the correlation between network latency, quantum key efficiency, and error rates, thereby plotting the contribution of quantum cryptography to the security of modern communication infrastructure in the future. Theory and practice, as exemplified in experimentation with quantum-computing software and numerical modelling, converge in this article to introduce possible future limits on using quantum cryptography as a nascent next-generation paradigm for cybersecurity.
Keywords: Quantum Cryptography; Cybersecurity Protocols; Quantum Key Distribution (QKD); Encryption Protocols; Next-Generation Security; Error Rates; Network Latency; Emerging Technologies.
Received: 19/04/2024, Revised: 06/06/2024, Accepted: 28/07/2024, Published: 01/03/2025
DOI: 10.64091/ATICL.2025.000093
AVE Trends in Intelligent Computer Letters, 2025 Vol. 1 No. 1 , Pages: 21-30