Few-Shot network intrusion detection based on prototypical capsule network with attention mechanism

Handi Sun, Liang Wan, Mengying Liu and Bo Wang

PLOS ONE, 2023, vol. 18, issue 4, 1-18

Abstract: Network intrusion detection plays a crucial role in ensuring network security by distinguishing malicious attacks from normal network traffic. However, imbalanced data affects the performance of intrusion detection system. This paper utilizes few-shot learning to solve the data imbalance problem caused by insufficient samples in network intrusion detection, and proposes a few-shot intrusion detection method based on prototypical capsule network with the attention mechanism. Our method is mainly divided into two parts, a temporal-spatial feature fusion method using capsules for feature extraction and a prototypical network classification method with attention and vote mechanisms. The experimental results demonstrate that our proposed model outperforms state-of-the-art methods on imbalanced datasets.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0284632

DOI: 10.1371/journal.pone.0284632

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