Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385452303> ?p ?o ?g. }
Showing items 1 to 92 of
92
with 100 items per page.
- W4385452303 abstract "In a WSN, sensors are always collecting information and transmitting it to other nodes. Their primary uses are in fields like defense, smart city development, and agricultural monitoring. The WSN needs to perform at a premium for these uses. Yet, there are many potential security concerns that could compromise a WSN's performance. Any interference with the WSN could severely degrade its functionality and lead to catastrophic failures. As a result, having the ability to quickly identify and stop intrusions is crucial. The goal of this proposed is to use a GRU-CNN model for quick detection and prevention of any intrusion. After receiving the input, the proposed method uses normalization and discretization for preprocessing the data, PSO (Particle Swarm Optimization) for feature extraction, CFS for feature selection and finally training the model by CNN-GRU. To better detect intrusions in wireless sensor networks, a GRU-CNN hybrid neural network model was presented; although the CNN module is responsible for extracting the feature vector from other high-dimensional data, the GRU module is responsible for from time sequence data to extract the feature vector." @default.
- W4385452303 created "2023-08-02" @default.
- W4385452303 creator A5000318557 @default.
- W4385452303 creator A5013476585 @default.
- W4385452303 creator A5013960740 @default.
- W4385452303 creator A5025607011 @default.
- W4385452303 creator A5036032398 @default.
- W4385452303 creator A5092266789 @default.
- W4385452303 date "2023-06-01" @default.
- W4385452303 modified "2023-09-26" @default.
- W4385452303 title "Wireless Sensor Network-based Intrusion Detection Technique using Deep Learning Approach of CNN-GRU" @default.
- W4385452303 cites W185358023 @default.
- W4385452303 cites W1964825150 @default.
- W4385452303 cites W2007659052 @default.
- W4385452303 cites W2010470943 @default.
- W4385452303 cites W2014061869 @default.
- W4385452303 cites W2031362032 @default.
- W4385452303 cites W2042163033 @default.
- W4385452303 cites W2091618476 @default.
- W4385452303 cites W2099580329 @default.
- W4385452303 cites W2133140680 @default.
- W4385452303 cites W2144092819 @default.
- W4385452303 cites W2150847526 @default.
- W4385452303 cites W2161253112 @default.
- W4385452303 cites W2162864159 @default.
- W4385452303 cites W2173462683 @default.
- W4385452303 cites W2508729862 @default.
- W4385452303 cites W2913497771 @default.
- W4385452303 cites W2919650678 @default.
- W4385452303 cites W2999988394 @default.
- W4385452303 cites W3011149747 @default.
- W4385452303 cites W3105682467 @default.
- W4385452303 cites W3147167903 @default.
- W4385452303 doi "https://doi.org/10.1109/icces57224.2023.10192844" @default.
- W4385452303 hasPublicationYear "2023" @default.
- W4385452303 type Work @default.
- W4385452303 citedByCount "0" @default.
- W4385452303 crossrefType "proceedings-article" @default.
- W4385452303 hasAuthorship W4385452303A5000318557 @default.
- W4385452303 hasAuthorship W4385452303A5013476585 @default.
- W4385452303 hasAuthorship W4385452303A5013960740 @default.
- W4385452303 hasAuthorship W4385452303A5025607011 @default.
- W4385452303 hasAuthorship W4385452303A5036032398 @default.
- W4385452303 hasAuthorship W4385452303A5092266789 @default.
- W4385452303 hasConcept C10551718 @default.
- W4385452303 hasConcept C119857082 @default.
- W4385452303 hasConcept C124101348 @default.
- W4385452303 hasConcept C136886441 @default.
- W4385452303 hasConcept C144024400 @default.
- W4385452303 hasConcept C148483581 @default.
- W4385452303 hasConcept C153180895 @default.
- W4385452303 hasConcept C154945302 @default.
- W4385452303 hasConcept C19165224 @default.
- W4385452303 hasConcept C24590314 @default.
- W4385452303 hasConcept C31258907 @default.
- W4385452303 hasConcept C35525427 @default.
- W4385452303 hasConcept C41008148 @default.
- W4385452303 hasConcept C52622490 @default.
- W4385452303 hasConcept C83665646 @default.
- W4385452303 hasConcept C85617194 @default.
- W4385452303 hasConceptScore W4385452303C10551718 @default.
- W4385452303 hasConceptScore W4385452303C119857082 @default.
- W4385452303 hasConceptScore W4385452303C124101348 @default.
- W4385452303 hasConceptScore W4385452303C136886441 @default.
- W4385452303 hasConceptScore W4385452303C144024400 @default.
- W4385452303 hasConceptScore W4385452303C148483581 @default.
- W4385452303 hasConceptScore W4385452303C153180895 @default.
- W4385452303 hasConceptScore W4385452303C154945302 @default.
- W4385452303 hasConceptScore W4385452303C19165224 @default.
- W4385452303 hasConceptScore W4385452303C24590314 @default.
- W4385452303 hasConceptScore W4385452303C31258907 @default.
- W4385452303 hasConceptScore W4385452303C35525427 @default.
- W4385452303 hasConceptScore W4385452303C41008148 @default.
- W4385452303 hasConceptScore W4385452303C52622490 @default.
- W4385452303 hasConceptScore W4385452303C83665646 @default.
- W4385452303 hasConceptScore W4385452303C85617194 @default.
- W4385452303 hasLocation W43854523031 @default.
- W4385452303 hasOpenAccess W4385452303 @default.
- W4385452303 hasPrimaryLocation W43854523031 @default.
- W4385452303 hasRelatedWork W1977222486 @default.
- W4385452303 hasRelatedWork W1991269640 @default.
- W4385452303 hasRelatedWork W2109563611 @default.
- W4385452303 hasRelatedWork W2152742912 @default.
- W4385452303 hasRelatedWork W2772780115 @default.
- W4385452303 hasRelatedWork W3036148153 @default.
- W4385452303 hasRelatedWork W4235480743 @default.
- W4385452303 hasRelatedWork W4243126553 @default.
- W4385452303 hasRelatedWork W2345184372 @default.
- W4385452303 hasRelatedWork W3088819897 @default.
- W4385452303 isParatext "false" @default.
- W4385452303 isRetracted "false" @default.
- W4385452303 workType "article" @default.