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1 Ergebnisse
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Leveraging n-gram neural embeddings to improve deep learnin..:
, In:
Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
,
Morbidoni, Christian
;
Spalazzi, Luca
;
Teti, Antonio
. - p. 995-1004 , 2022
Link:
https://dl.acm.org/doi/10.1145/3477314.3507269
RT T1 <cTitle>Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing</cTitle>: T1 <Title>Leveraging n-gram neural embeddings to improve deep learning DGA detection</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3507269&Exemplar=1&LAN=DE A1 Morbidoni, Christian A1 Spalazzi, Luca A1 Teti, Antonio A1 Cucchiarelli, Alessandro PB ACM YR 2022 K1 LSTM K1 deep learning K1 domain generation algorithms K1 n-grams K1 neural embeddings K1 Security and privacy K1 Intrusion/anomaly detection and malware mitigation K1 Intrusion detection systems K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Supervised learning K1 Supervised learning by classification K1 Machine learning approaches K1 Neural networks K1 Malware and its mitigation SP 995 OP 1004 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3477314.3507269 DO https://dl.acm.org/doi/10.1145/3477314.3507269 SF ELIB - SuUB Bremen
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