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@inproceedings{1875897,
author = {Bangui, Hind and Rossi, Bruno and Bühnová, Barbora},
address = {New York, USA},
booktitle = {The 38th IEEE International Conference on Software Maintenance and Evolution},
doi = {http://dx.doi.org/10.1109/ICSME55016.2022.00040},
keywords = {Critical Infrastructures; Microservices; Antifragility;Machine Learning;Generative Adversarial Network},
howpublished = {elektronická verze "online"},
language = {eng},
location = {New York, USA},
isbn = {978-1-6654-7956-1},
pages = {364-368},
publisher = {IEEE},
title = {A Conceptual Antifragile Microservice Framework for Reshaping Critical Infrastructures},
url = {https://ieeexplore.ieee.org/abstract/document/9977445},
year = {2022}
}
TY - JOUR
ID - 1875897
AU - Bangui, Hind - Rossi, Bruno - Bühnová, Barbora
PY - 2022
TI - A Conceptual Antifragile Microservice Framework for Reshaping Critical Infrastructures
PB - IEEE
CY - New York, USA
SN - 9781665479561
KW - Critical Infrastructures
KW - Microservices
KW - Antifragility;Machine Learning;Generative Adversarial Network
UR - https://ieeexplore.ieee.org/abstract/document/9977445
N2 - 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.
ER -
BANGUI, Hind, Bruno ROSSI and Barbora BÜHNOVÁ. A Conceptual Antifragile Microservice Framework for Reshaping Critical Infrastructures. Online. In \textit{The 38th IEEE International Conference on Software Maintenance and Evolution}. New York, USA: IEEE, 2022, p.~364-368. ISBN~978-1-6654-7956-1. Available from: https://dx.doi.org/10.1109/ICSME55016.2022.00040.
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