@inproceedings{9d29c3c406004f6f917819fb32ea204a,
title = "Model Driven Engineering for Resilience of Systems with Black Box and AI-based Components",
abstract = "Modern complex cyber-physical systems heavily rely on humans and AI for mission-critical operations and decision making. Unfortunately, these components are often 'black boxes' to the operator, either because the decision models are too complex for human comprehension (e.g. deep neural networks) or are intentionally hidden (e.g. proprietary intellectual property). In these cases, the decision logic cannot be validated and therefore trust is forced.",
keywords = "AI, Black Box Components, Defense in Depth, Model Driven Engineering, Resilience, Safety, Security",
author = "Nikolaos Papakonstantinou and Britta Hale and Joonas Linnosmaa and Jarno Salonen and Bossuyt, {Douglas L.Van}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 68th Annual Reliability and Maintainability Symposium, RAMS 2022, RAMS 2022 ; Conference date: 24-01-2022 Through 27-01-2022",
year = "2022",
month = sep,
day = "20",
doi = "10.1109/RAMS51457.2022.9893930",
language = "English",
series = "Proceedings - Annual Reliability and Maintainability Symposium",
publisher = "IEEE Institute of Electrical and Electronic Engineers",
booktitle = "68th Annual Reliability and Maintainability Symposium, RAMS 2022",
address = "United States",
}