Privacy-Aware Machine Learning in Microservices Architecture for AI Applications Built on Federated Digital Infrastructure Platforms
Keywords:
Privacy-aware computing, microservices, machine learning, federated infrastructure, secure AI, decentralized learning, digital sovereignty, service architecture, federated learning, privacy complianceAbstract
The integration of machine learning into microservices architectures within federated digital infrastructure platforms has ushered in a new era of distributed artificial intelligence. This paradigm shift offers significant scalability and modularity advantages, yet presents acute challenges in data privacy. This paper explores a privacy-aware approach to deploying machine learning models in microservice-based AI ecosystems that operate over federated infrastructures. We analyze architectural considerations, privacy-preserving techniques, and real-world applications. Emphasis is placed on decentralized data handling, secure inference protocols, and federated learning. The research also investigates the implications of platform heterogeneity and regulatory constraints..
References
Amini, M. H., Arasteh, H., & Siano, P. (2018). Sustainable smart cities through the lens of complex interdependent infrastructures. Springer.
Bao, K., Mauser, I., Kochanneck, S., & Xu, H. (2016). A microservice architecture for the intranet of things. ACM. https://doi.org/10.1145/3007203.3007215
Eikermann, R., Look, M., Roth, A., & Rumpe, B. (2017). Architecting cloud services for the digital me. Elsevier.
Gummadi, V. P. K. (2019). Microservices architecture with APIs: Design, implementation, and MuleSoft integration. Journal of Electrical Systems, 15(4), 130–134. https://doi.org/10.52783/jes.9328
Friese, I., Copeland, R., & Göndör, S. (2017). Cross-domain discovery of communication peers. IEEE. https://arxiv.org/pdf/1704.08957
Huang, D., & Wu, H. (2017). Mobile cloud computing: foundations and service models. Morgan Kaufmann.
Mistrík, I., Bahsoon, R., Ali, N., Heisel, M., & Maxim, B. (2017). Software architecture for big data and the cloud. Elsevier.
Ranjan, R., Rana, O., Nepal, S., & Yousif, M. (2018). The next grand challenges: IoT and data science. IEEE. https://ieeexplore.ieee.org/abstract/document/8383659/
Suzic, B., Prünster, B., Ziegler, D., & Marsalek, A. (2016). Balancing utility and security in federated cloud systems. Springer.
Sweeney, L. (2002). k-Anonymity: A model for protecting privacy. Int. Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(5), 557–570. https://doi.org/10.1142/S0218488502001648
Westerlund, M., & Enkvist, J. (2016). Platform privacy and data protection. JIPITEC. https://www.jipitec.eu/jipitec/article/view/167/162
