2022
DOI: 10.1155/2022/3317048
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Few-Shot Learning-Based Network Intrusion Detection through an Enhanced Parallelized Triplet Network

Abstract: Network intrusion detection is one of the critical techniques to enhance cybersecurity. Several few-shot learning-based methods have recently been proposed to alleviate the dependence on large training samples in many supervised learning methods. However, it is still a challenge to achieve real-time higher-accuracy intrusion detection which is an essential requirement for high-speed network security. In this study, we propose a novel few-shot learning-based network intrusion detection method to address this ch… Show more

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Cited by 6 publications
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References 35 publications
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