RITUAL: a Platform Quantifying the Trustworthiness of Supervised Machine Learning
Published in 2022 18th International Conference on Network and Service Management (CNSM), 364-366, 2022
This demo presents RITUAL, a platform composed of a novel algorithm and a Web application quantifying the trustworthiness level of supervised Machine and Deep Learning (ML/DL) models according to their fairness, explainability, robustness, and accountability. The algorithm is deployed on a Web application to allow users to quantify and compare the trustworthiness of their ML/DL models. Finally, a scenario with ML/DL models classifying network cyberattacks demonstrates the platform applicability.
Recommended citation: Huertas Celdrán, Alberto, Bauer, Jan, Demirci, Melike, Leupp, Joel, Franco, Muriel Figueredo, Sánchez Sánchez, Pedro Miguel, Bovet, Gérôme, Martínez Pérez, Gregorio, & Stiller, Burkhard. (2022). "RITUAL: a Platform Quantifying the Trustworthiness of Supervised Machine Learning." 2022 18th International Conference on Network and Service Management (CNSM), 364-366.
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