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pro vyhledávání: '"Marfo, William"'
Modern vehicles rely on a myriad of electronic control units (ECUs) interconnected via controller area networks (CANs) for critical operations. Despite their ubiquitous use and reliability, CANs are susceptible to sophisticated cyberattacks, particul
Externí odkaz:
http://arxiv.org/abs/2408.05427
Due to the veracity and heterogeneity in network traffic, detecting anomalous events is challenging. The computational load on global servers is a significant challenge in terms of efficiency, accuracy, and scalability. Our primary motivation is to i
Externí odkaz:
http://arxiv.org/abs/2303.07452
Publikováno v:
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 14, No. 2, 2023
In this research, we focus on the usage of adversarial sampling to test for the fairness in the prediction of deep neural network model across different classes of image in a given dataset. While several framework had been proposed to ensure robustne
Externí odkaz:
http://arxiv.org/abs/2303.02874
The modern industrial environment is equipping myriads of smart manufacturing machines where the state of each device can be monitored continuously. Such monitoring can help identify possible future failures and develop a cost-effective maintenance p
Externí odkaz:
http://arxiv.org/abs/2301.09030
Publikováno v:
Geosciences (2076-3263); Sep2024, Vol. 14 Issue 9, p232, 20p
Publikováno v:
2022 17th Annual System of Systems Engineering Conference (SOSE).
The modern industrial environment is equipping myriads of smart manufacturing machines where the state of each device can be monitored continuously. Such monitoring can help identify possible future failures and develop a cost-effective maintenance p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d69cf9a9ec09d0be297bc9e5d6e0d98a
https://doi.org/10.1109/sose55472.2022.9812638
https://doi.org/10.1109/sose55472.2022.9812638