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1 Ergebnisse
1
Federated Explainability for Network Anomaly Characterizati..:
, In:
Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses
,
Sáez-de-Cámara, Xabier
;
Flores, Jose Luis
;
Arellano, Cristóbal
.. - p. 346-365 , 2023
Link:
https://dl.acm.org/doi/10.1145/3607199.3607234
RT T1 <cTitle>Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses</cTitle>: T1 <Title>Federated Explainability for Network Anomaly Characterization</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3607234&Exemplar=1&LAN=DE A1 Sáez-de-Cámara, Xabier A1 Flores, Jose Luis A1 Arellano, Cristóbal A1 Urbieta, Aitor A1 Zurutuza, Urko PB ACM YR 2023 K1 IoT security K1 SIEM K1 explainable artificial intelligence K1 federated learning K1 Security and privacy K1 Intrusion/anomaly detection and malware mitigation K1 Intrusion detection systems K1 Computing methodologies K1 Artificial intelligence K1 Distributed artificial intelligence K1 Cooperation and coordination K1 Machine learning K1 Learning paradigms K1 Unsupervised learning K1 Systems security K1 Distributed systems security SP 346 OP 365 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3607199.3607234 DO https://dl.acm.org/doi/10.1145/3607199.3607234 SF ELIB - SuUB Bremen
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