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Titlebook: Machine Learning for Networking; Second IFIP TC 6 Int Selma Boumerdassi,éric Renault,Paul Mühlethaler Conference proceedings 2020 IFIP Inte

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樓主: Malinger
61#
發(fā)表于 2025-4-1 03:25:05 | 只看該作者
Towards a Hierarchical Deep Learning Approach for Intrusion Detection,ent resources. That is why this paper presents a new hierarchical method based on deep learning algorithms to deal with intrusion detection. This method has proven to be very effective across traditional implementation on four public datasets, and meets all the other requirements of an efficient intrusion detection system.
62#
發(fā)表于 2025-4-1 06:56:03 | 只看該作者
63#
發(fā)表于 2025-4-1 11:05:04 | 只看該作者
64#
發(fā)表于 2025-4-1 18:15:11 | 只看該作者
Q-routing: From the Algorithm to the Routing Protocol,n in 1994 based on Q-learning on the network simulator Qualnet. Twenty-five years later, we conclude that a more realistic implementation in more realistic network environment does not give always better Quality of Service than the historical Bellman-Ford protocol. We provide all the materials to conduct reproducible research.
65#
發(fā)表于 2025-4-1 20:30:58 | 只看該作者
66#
發(fā)表于 2025-4-1 23:04:57 | 只看該作者
Space-Time Pattern Extraction in Alarm Logs for Network Diagnosis,ay be huge, and thus hardly readable for experts. To circumvent this problem, this paper proposes a framework allowing to query a DIG-DAG in order to extract patterns of interest, and a full methodology for end-to-end analysis of a log.
67#
發(fā)表于 2025-4-2 05:44:51 | 只看該作者
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