Towards improving explainability, resilience and performance of cybersecurity analysis of 5G/IoT networks - Archive ouverte HAL
Communication Dans Un Congrès Année : 2022

Towards improving explainability, resilience and performance of cybersecurity analysis of 5G/IoT networks

Résumé

Artificial Intelligence (AI) is envisioned to play a critical role in controlling and orchestrating 5G/IoT networks and their applications, thanks to its capabilities to recognize abnormal patterns in complex situations and produce accurate decisions. However, AI models are vulnerable to adversarial attacks, thus the societal view is far from trustworthy as to its usage in safety critical areas relying on 5G/IoT networks. In this paper, we present ongoing work being done in the H2020 SPATIAL project that targets developing and evaluating AI-based modules for anomaly detection and Root Cause Analysis in the 5G/IoT context regarding different criteria, such as explainability, resilience and performance on a real 5G/IoT testbed.
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Dates et versions

hal-04477901 , version 1 (26-02-2024)

Identifiants

Citer

Manh-Dung Nguyen, Vinh Hoa La, Ana R Cavalli, Edgardo Montes De Oca. Towards improving explainability, resilience and performance of cybersecurity analysis of 5G/IoT networks. 2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), Mälardalen University, Apr 2022, Valencia (Espagne), Spain. ⟨10.1109/ICSTW55395.2022.00016⟩. ⟨hal-04477901⟩
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