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Outlier detection is an important research direction in data mining. This paper mainly applies outlier detection algorithm in intrusion detection, and proposes a novel outlier detection algorithm based on neighbor propagation clustering. The proposed algorithm first clusters the original dataset, then calculates the outlier degree, and finally mines the intrusion behaviors. To verify its effectiveness, our algorithm was tested on public dataset on network intrusions. The results prove that ourdoi:10.18280/ria.340311 fatcat:eu7pc2lo6jb6heluvkbnnabt4e