A quantitative framework for network resilience evaluation using Dynamic Bayesian Network
S Jiang, L Yang, G Cheng, X Gao, T Feng… - Computer …, 2022 - Elsevier
Measuring and evaluating network resilience has become an important aspect since the
network is vulnerable to both uncertain disturbances and malicious attacks. Networked …
network is vulnerable to both uncertain disturbances and malicious attacks. Networked …
A Quantitative Framework for Network Resilience Evaluation using Dynamic Bayesian Network
S Jiang, L Yang, G Cheng, X Gao, T Feng… - arXiv preprint arXiv …, 2021 - arxiv.org
Measuring and evaluating network resilience has become an important aspect since the
network is vulnerable to both uncertain disturbances and malicious attacks. Networked …
network is vulnerable to both uncertain disturbances and malicious attacks. Networked …
A Quantitative Framework for Network Resilience Evaluation using Dynamic Bayesian Network
S Jiang, L Yang, G Cheng, X Gao, T Feng… - arXiv e …, 2021 - ui.adsabs.harvard.edu
Measuring and evaluating network resilience has become an important aspect since the
network is vulnerable to both uncertain disturbances and malicious attacks. Networked …
network is vulnerable to both uncertain disturbances and malicious attacks. Networked …
[PDF][PDF] A Quantitative Framework for Network Resilience Evaluation using Dynamic Bayesian Network
S Jiang, L Yang, G Cheng, X Gao, T Feng, Y Zhou - researchgate.net
Measuring and evaluating network resilience has become an important aspect since the
network is vulnerable to both uncertain disturbances and malicious attacks. Networked …
network is vulnerable to both uncertain disturbances and malicious attacks. Networked …