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Chen et al., 2021 - Google Patents

An efficient network intrusion detection model based on temporal convolutional networks

Chen et al., 2021

Document ID
11077817552371791425
Author
Chen J
Yin S
Cai S
Zhang C
Yin Y
Zhou L
Publication year
Publication venue
2021 IEEE 21st International Conference on Software Quality, Reliability and Security (QRS)

External Links

Snippet

Network intrusion detection plays an important role in the network security, but the increasingly complex network environment brings a serious challenge to intrusion detection. Although the existing efficient Convolutional Neural Network (CNN)-based network traffic …
Continue reading at ieeexplore.ieee.org (other versions)

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    • G06K9/6267Classification techniques
    • G06K9/6279Classification techniques relating to the number of classes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
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    • GPHYSICS
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    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
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