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dc.contributor.authorElgazazz, Areeg Samir Ahmed
dc.contributor.authorDagenborg, Håvard Johansen
dc.date.accessioned2023-11-13T12:47:00Z
dc.date.available2023-11-13T12:47:00Z
dc.date.issued2023-10-12
dc.description.abstractKubernetes default configurations do not always provide optimal security and performance for all clusters and IoT edge devices deployed, affecting the scalability of a given workload and making them vulnerable to security breaches and information leakage if misconfigured. We present an adaptive controller to identify the type of misconfiguration and its consequence threat to optimize the system behavior. Our work differs from existing approaches as it is fully automated and can diagnose various errors on the fly. The controller is evaluated in terms of quality and accuracy of identification. The results show that the controller can identify around 90% of the total number of configuration values with a reasonable average identification overhead.en_US
dc.identifier.citationSamir, A., Dagenborg, H. (2023). Adaptive Controller to Identify Misconfigurations and Optimize the Performance of Kubernetes Clusters and IoT Edge Devices. In: Papadopoulos, G.A., Rademacher, F., Soldani, J. (eds) Service-Oriented and Cloud Computing. ESOCC 2023. Lecture Notes in Computer Science, vol 14183. Springer, Cham. https://doi.org/10.1007/978-3-031-46235-1_11en_US
dc.identifier.cristinIDFRIDAID 2194054
dc.identifier.doihttps://doi.org/10.1007/978-3-031-46235-1_11
dc.identifier.urihttps://hdl.handle.net/10037/31733
dc.language.isoengen_US
dc.publisherSpringer Natureen_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.titleAdaptive Controller to Identify Misconfigurations and Optimize the Performance of Kubernetes Clusters and IoT Edge Devicesen_US
dc.type.versionacceptedVersionen_US
dc.typeConference objecten_US
dc.typeKonferansebidragen_US


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