FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4321366940> ?p ?o ?g. }

• W4321366940 endingPage "18" @default.
• W4321366940 startingPage "1" @default.
• W4321366940 abstract "As the network is closely related to people’s daily life, network security has become an important factor affecting the physical and mental health of human beings. Network flow classification is the foundation of network security. It is the basis for providing various network services such as network security maintenance, network monitoring, and network quality of service (QoS). Therefore, this field has always been a hot spot of academic and industrial research. Existing studies have shown that through appropriate data preprocessing techniques, machine learning methods can be used to classify network flows, most of which, however, are based on manually and expert-originated feature sets; it is a time-consuming and laborious work. Moreover, only features extracted by a single model can be used in classification tasks, which can easily make the model inefficient and prone to overfitting. In order to solve the abovementioned problems, this study proposes a multimodal automatic analysis framework based on spatial and sequential features. The framework is completely based on the deep learning method and realizes automatic extraction of two types of features, which is very suitable for processing large-flow information; this improves the efficiency of network flow classification. There are two types of frameworks based on pretraining and joint-training, respectively, with analyzing the advantages and disadvantages of them in practice. In terms of evaluation, compared with the previous methods, the experimental results show that the framework has good performance in both accuracy and stability." @default.
• W4321366940 created "2023-02-21" @default.
• W4321366940 creator A5004475299 @default.
• W4321366940 creator A5045296698 @default.
• W4321366940 creator A5048147530 @default.
• W4321366940 creator A5058835260 @default.
• W4321366940 creator A5062579716 @default.
• W4321366940 creator A5067743408 @default.
• W4321366940 creator A5070719054 @default.
• W4321366940 creator A5074186449 @default.
• W4321366940 creator A5076368319 @default.
• W4321366940 date "2023-02-20" @default.
• W4321366940 modified "2023-10-14" @default.
• W4321366940 title "A Multimodal Network Security Framework for Healthcare Based on Deep Learning" @default.
• W4321366940 cites W1988790447 @default.
• W4321366940 cites W2062401262 @default.
• W4321366940 cites W2073089243 @default.
• W4321366940 cites W2613715541 @default.
• W4321366940 cites W2745051817 @default.
• W4321366940 cites W2750674396 @default.
• W4321366940 cites W2890902148 @default.
• W4321366940 cites W2900853407 @default.
• W4321366940 cites W2904542630 @default.
• W4321366940 cites W2912386632 @default.
• W4321366940 cites W2917091861 @default.
• W4321366940 cites W2921165530 @default.
• W4321366940 cites W2963516518 @default.
• W4321366940 cites W2978116268 @default.
• W4321366940 cites W2995207481 @default.
• W4321366940 cites W3038397330 @default.
• W4321366940 cites W3119167162 @default.
• W4321366940 cites W3160694286 @default.
• W4321366940 cites W3190219082 @default.
• W4321366940 cites W4212883601 @default.
• W4321366940 doi "https://doi.org/10.1155/2023/9041355" @default.
• W4321366940 hasPublicationYear "2023" @default.
• W4321366940 type Work @default.
• W4321366940 citedByCount "0" @default.
• W4321366940 crossrefType "journal-article" @default.
• W4321366940 hasAuthorship W4321366940A5004475299 @default.
• W4321366940 hasAuthorship W4321366940A5045296698 @default.
• W4321366940 hasAuthorship W4321366940A5048147530 @default.
• W4321366940 hasAuthorship W4321366940A5058835260 @default.
• W4321366940 hasAuthorship W4321366940A5062579716 @default.
• W4321366940 hasAuthorship W4321366940A5067743408 @default.
• W4321366940 hasAuthorship W4321366940A5070719054 @default.
• W4321366940 hasAuthorship W4321366940A5074186449 @default.
• W4321366940 hasAuthorship W4321366940A5076368319 @default.
• W4321366940 hasBestOaLocation W43213669401 @default.
• W4321366940 hasConcept C108583219 @default.
• W4321366940 hasConcept C111472728 @default.
• W4321366940 hasConcept C112972136 @default.
• W4321366940 hasConcept C119857082 @default.
• W4321366940 hasConcept C124101348 @default.
• W4321366940 hasConcept C138885662 @default.
• W4321366940 hasConcept C154945302 @default.
• W4321366940 hasConcept C202444582 @default.
• W4321366940 hasConcept C22019652 @default.
• W4321366940 hasConcept C2776401178 @default.
• W4321366940 hasConcept C2779530757 @default.
• W4321366940 hasConcept C31258907 @default.
• W4321366940 hasConcept C33923547 @default.
• W4321366940 hasConcept C34736171 @default.
• W4321366940 hasConcept C41008148 @default.
• W4321366940 hasConcept C41895202 @default.
• W4321366940 hasConcept C50644808 @default.
• W4321366940 hasConcept C5119721 @default.
• W4321366940 hasConcept C52622490 @default.
• W4321366940 hasConcept C9652623 @default.
• W4321366940 hasConceptScore W4321366940C108583219 @default.
• W4321366940 hasConceptScore W4321366940C111472728 @default.
• W4321366940 hasConceptScore W4321366940C112972136 @default.
• W4321366940 hasConceptScore W4321366940C119857082 @default.
• W4321366940 hasConceptScore W4321366940C124101348 @default.
• W4321366940 hasConceptScore W4321366940C138885662 @default.
• W4321366940 hasConceptScore W4321366940C154945302 @default.
• W4321366940 hasConceptScore W4321366940C202444582 @default.
• W4321366940 hasConceptScore W4321366940C22019652 @default.
• W4321366940 hasConceptScore W4321366940C2776401178 @default.
• W4321366940 hasConceptScore W4321366940C2779530757 @default.
• W4321366940 hasConceptScore W4321366940C31258907 @default.
• W4321366940 hasConceptScore W4321366940C33923547 @default.
• W4321366940 hasConceptScore W4321366940C34736171 @default.
• W4321366940 hasConceptScore W4321366940C41008148 @default.
• W4321366940 hasConceptScore W4321366940C41895202 @default.
• W4321366940 hasConceptScore W4321366940C50644808 @default.
• W4321366940 hasConceptScore W4321366940C5119721 @default.
• W4321366940 hasConceptScore W4321366940C52622490 @default.
• W4321366940 hasConceptScore W4321366940C9652623 @default.
• W4321366940 hasFunder F4320321001 @default.
• W4321366940 hasLocation W43213669401 @default.
• W4321366940 hasOpenAccess W4321366940 @default.
• W4321366940 hasPrimaryLocation W43213669401 @default.
• W4321366940 hasRelatedWork W2989932438 @default.
• W4321366940 hasRelatedWork W3035162004 @default.
• W4321366940 hasRelatedWork W3099765033 @default.
• W4321366940 hasRelatedWork W4210794429 @default.
• W4321366940 hasRelatedWork W4223943233 @default.

• next