Quantum API Gateways: Exploring the Future of Secure and Scalable Communication in Quantum Computing Environments
DOI:
https://doi.org/10.32628/CSEIT25113373Keywords:
Quantum Computing, Environments, Information, Development, Management, StandardizedAbstract
As quantum computing advances, the need for secure and scalable communication in quantum environments becomes increasingly important. Quantum API Gateways have emerged as a promising solution to address this challenge. These gateways bridge classical and quantum communication, enabling the secure transfer of information between classical and quantum systems. Through advanced cryptographic techniques and quantum key distribution protocols, Quantum API Gateways provide high security for data transmission in quantum computing environments. They also offer a scalable approach, allowing for the seamless integration of quantum applications with existing classical systems. It enables the development of hybrid quantum-classical systems, which are crucial for harnessing the full potential of quantum computing. Quantum API Gateways allow for the efficient and reliable management of quantum resources, such as quantum processors and channels, by providing a standardized interface for developers to access this resource.
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Moguel, E., Rojo, J., Valencia, D., Berrocal, J., Garcia-Alonso, J., & Murillo, J. M. (2022). Quantum service-oriented computing: current landscape and challenges. Software Quality Journal, 30(4), 983-1002.
Moguel, E., Garcia-Alonso, J., & Murillo, J. M. (2024). Development and Deployment of Quantum Services. In Quantum Software: Aspects of Theory and System Design (pp. 189-222). Cham: Springer Nature Switzerland.
Mahalingam, P. R. (2022). A Conceptual Framework for Scaling and Security in Serverless Environments Using Blockchain and Quantum Key Distribution. In Quantum and Blockchain for Modern Computing Systems: Vision and Advancements: Quantum and Blockchain Technologies: Current Trends and Challenges (pp. 157-182). Cham: Springer International Publishing.
Karim Eddin, S., Salloum, H., Shahin, M. N., Salloum, B., Mazzara, M., & Reza Bahrami, M. (2024, April). Quantum microservices: transforming software architecture with quantum computing. In International Conference on Advanced Information Networking and Applications (pp. 227-237). Cham: Springer Nature Switzerland.
Moguel Márquez, J. E., Rojo Martin, F. J., Valencia Corrales, D., Berrocal Olmeda, J. J., García Alonso, J. M., & Murillo Rodríguez, J. M. (2022). Quantum service-oriented computing: current landscape and challenges.
Romero‐Álvarez, J., Alvarado‐Valiente, J., Moguel, E., Garcia‐Alonso, J., & Murillo, J. M. (2024). Enabling continuous deployment techniques for quantum services. Software: Practice and Experience, 54(8), 1491-1515.
Edwards, M. (2020). Towards Practical Hybrid Quantum/Classical Computing (Master's thesis, University of Waterloo).
Vasani, V., Prateek, K., Amin, R., Maity, S., & Dwivedi, A. D. (2024). Embracing the quantum frontier: Investigating quantum communication, cryptography, applications and future directions. Journal of Industrial Information Integration, 100594.
Nguyen, H. T., Usman, M., & Buyya, R. (2024). iQuantum: A toolkit for modeling and simulation of quantum computing environments. Software: Practice and Experience, 54(6), 1141-1171.
van Deventer, O., Spethmann, N., Loeffler, M., Amoretti, M., van den Brink, R., Bruno, N., ... & Wilhelm-Mauch, F. K. (2022). Towards European standards for quantum technologies. EPJ Quantum Technology, 9(1), 33.
Amoretti, M., Pecori, R., Protskaya, Y., Veltri, L., & Zanichelli, F. (2020). A scalable and secure publish/subscribe-based framework for industrial IoT. IEEE Transactions on Industrial Informatics, 17(6), 3815-3825.
Prateek, K., & Maity, S. (2022). Post‐quantum blockchain–enabled services in scalable smart cities. Quantum Blockchain: An Emerging Cryptographic Paradigm, 263-291.
Murillo, J. M., Garcia-Alonso, J., Moguel, E., Barzen, J., Leymann, F., Ali, S., ... & Wimmer, M. (2024). Challenges of quantum software engineering for the next decade: The road ahead. arXiv preprint arXiv:2404.06825.
Halak, B., Csete, C. S., Joyce, E., Papaioannou, J., Pires, A., Soma, J., ... & Murphy, M. (2024). A Security Assessment tool for Quantum Threat Analysis. arXiv preprint arXiv:2407.13523.
Kolachana, V., Upmandewan, D., Giri, A., Pavan, N., Ahmed, A., Thippeswamy, M. N., & Vinay, T. R. (2022, March). Application of Quantum Algorithms for Network Protocols. In Proceedings of Third International Conference on Communication, Computing and Electronics Systems: ICCCES 2021 (pp. 439-461). Singapore: Springer Singapore.
Kundu, S., & Ghosh, S. (2024). Security Concerns in Quantum Machine Learning as a Service. arXiv preprint arXiv:2408.09562.
Sikeridis, D., Ott, D., Huntley, S., Sharma, S., Dhanasekar, V. K., Bansal, M., ... & Veeraswamy, S. (2023). ELCA: Introducing Enterprise-level Cryptographic Agility for a Post-Quantum Era. Cryptology ePrint Archive.
Kourtis, M. A., Domingo, D., Tcholtchev, N., Markakis, E. K., Niemiec, M., ... & Stoianov, N. (2024, July). PQ-REACT: Post Quantum Cryptography Framework for Energy Aware Contexts. In Proceedings of the 19th International Conference on Availability, Reliability and Security (pp. 1-7).
V. L. B. Sunkara, "An Intelligent Routing Framework for High-Traffic Networks using Deep Learning," Int. J. Innov. Res. Comput. Commun. Eng., vol. 13, no. 3, pp. 1942–1949, 2025, doi: 10.15680/IJIRCCE.2025.1303002.
Mohanty, J. P., & Mahapatra, K. (2023, August). Quantum Gateway Security with Fault Tolerance. In 2023 International Conference on Electrical, Electronics, Communication and Computers (ELEXCOM) (pp. 1-6). IEEE.
Nguyen, H. T., Pham, B. B. A., Usman, M., & Buyya, R. (2024). Quantum Serverless Paradigm and Application Development using the QFaaS Framework. arXiv preprint arXiv:2407.02828.
Sharma, Pradeep & Logeshwaran, Jaganathan. (2024). Enhancing Credit Card Risk Management through Real-Time Data Processing and Machine Learning Techniques.
A. Musunuri, "Automation at scale: An AI-first approach to data analysis," Int. J. Innov. Res. Comput. Commun. Eng., vol. 13, no. 4, pp. 3035–3043, 2025. [Online]. Available: https://doi.org/10.15680/IJIRCCE.2025.1304004.
V. R. Dabbir, "The role of machine learning in next-generation data processing pipelines," in Proc. Int. Conf. Commun. Smart Devices, 2025.
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