A Conceptual Antifragile Microservice Framework for Reshaping Critical Infrastructures

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This publication doesn't include Faculty of Medicine. It includes Faculty of Informatics. Official publication website can be found on muni.cz.


Year of publication 2022
Type Article in Proceedings
Conference The 38th IEEE International Conference on Software Maintenance and Evolution
MU Faculty or unit

Faculty of Informatics

Web https://ieeexplore.ieee.org/abstract/document/9977445
Doi http://dx.doi.org/10.1109/ICSME55016.2022.00040
Keywords Critical Infrastructures; Microservices; Antifragility;Machine Learning;Generative Adversarial Network
Description Recently, microservices have been examined as a solution for reshaping and improving the flexibility, scalability, and maintainability of critical infrastructure systems. However, microservice systems are also suffering from the presence of a substantial number of potentially vulnerable components that may threaten the protection of critical infrastructures. To address the problem, this paper proposes to leverage the concept of antifragility built in a framework for building self-learning microservice systems that could be strengthened by faults and threats instead of being deteriorated by them. To illustrate the approach, we instantiate the proposed approach of autonomous machine learning through an experimental evaluation on a benchmarking dataset of microservice faults.
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