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- W3206316291 abstract "In today’s society, computer network is one of the most important and advanced infrastructures. The emerging technologies, represented by cloud computing, have brought many new situations and challenges to network security. This paper presents a novel scheme, called BotCatcher, which is based on the fusion and optimization of two different types of existing methods for intrusion detection. There are two models in the scheme: 1) The high-speed mode based on complementary advantages improves the F-Measure by about 0.06 without reducing the detection rate and 2) The high-quality mode based on deep learning combines the historical behavior of hosts and optimizes the detection index for greater performance improvement." @default.
- W3206316291 created "2021-10-25" @default.
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- W3206316291 date "2021-08-01" @default.
- W3206316291 modified "2023-09-27" @default.
- W3206316291 title "BotCatcher:A Complementary Advantages and Deep Learning Based Scheme for Intrusion Detection" @default.
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- W3206316291 doi "https://doi.org/10.1109/ihmsc52134.2021.00030" @default.
- W3206316291 hasPublicationYear "2021" @default.
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