@inproceedings{5cd6c2ba0a164f24b4a08f2248bf9b07,
title = "Supervised Intrusion Detection with Out-of-Distribution Detection for Microservices",
abstract = "Microservice architecture enhances system flexibility and reliability but raises security concerns due to potential malicious attacks. We propose a supervised Out-of-Distribution (OOD) detector leveraging AI and ML to analyze container command sequences. Our technique identifies known and unknown attack patterns, employing out-of-distribution detection. Using a deep neural network, we learn features and minimize classification errors. Comparative evaluations demonstrate its efficacy, aiming to enhance container security and deepen insights into microservice attack behaviors.",
keywords = "Intrusion detection, microservice security, out-of-distribution detection",
author = "Chen, {Yong Syuan} and Lien, {Hsiang Yin} and Li, {Jo Yu} and Lin, {Chia Yu}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 11th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2024 ; Conference date: 09-07-2024 Through 11-07-2024",
year = "2024",
doi = "10.1109/ICCE-Taiwan62264.2024.10674502",
language = "???core.languages.en_GB???",
series = "11th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "121--122",
booktitle = "11th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2024",
}