Anomaly Detection with Partially Observed Anomaly Types

2021 2nd International Conference on Computer Communication and Network Security (CCNS)(2021)

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摘要
In this paper, we consider the problem of anomaly detection when a small number of anomaly types are observed. Previous research primarily focused on supervised learning, when all samples are labeled. And unsupervised learning is used, when all samples are unlabeled. However, many settings do not satisfy the above two situations. Recently, there are some studies on the situations that anomalies ar...
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关键词
Computational modeling,Supervised learning,Network security,Classification algorithms,Computer security,Anomaly detection,Unsupervised learning
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