Matches in SemOpenAlex for { <https://semopenalex.org/work/W3097192014> ?p ?o ?g. }
Showing items 1 to 76 of
76
with 100 items per page.
- W3097192014 endingPage "307" @default.
- W3097192014 startingPage "301" @default.
- W3097192014 abstract "Abstract Analyzing the runtime behaviors of Android apps is crucial for malware detection. In this paper, we attempt to learn the behavior level features of an app from function calls. The challenges of this task are twofold. First, the absence of function attributes hinders the understanding of app behaviors. Second, the graphical representation of function calls cannot be directly processed by classical machine learning algorithms. In this paper, we develop two methods to overcome these challenges. Based on function embedding, we first propose the concept of enhanced function call graphs (E-FCGs) to characterize app runtime behaviors. We then develop a Graph Convolutional Network (GCN) based algorithm to obtain vector representations of E-FCGs. Extensive experiments show that the features learned by our method can achieve surprisingly high detection performance on a variety of classifiers (e.g., LR, DT, SVM, KNN, RF, MLP and CNN), significantly outperforming the traditional static features." @default.
- W3097192014 created "2020-11-09" @default.
- W3097192014 creator A5008919430 @default.
- W3097192014 creator A5013466530 @default.
- W3097192014 creator A5013795174 @default.
- W3097192014 creator A5074663989 @default.
- W3097192014 creator A5081650208 @default.
- W3097192014 date "2021-01-01" @default.
- W3097192014 modified "2023-10-17" @default.
- W3097192014 title "Learning features from enhanced function call graphs for Android malware detection" @default.
- W3097192014 cites W2122672392 @default.
- W3097192014 cites W2575599800 @default.
- W3097192014 cites W2601621757 @default.
- W3097192014 cites W2612872092 @default.
- W3097192014 cites W2618621776 @default.
- W3097192014 cites W2782290149 @default.
- W3097192014 cites W2792310543 @default.
- W3097192014 cites W2885070483 @default.
- W3097192014 cites W2903488155 @default.
- W3097192014 cites W2943383044 @default.
- W3097192014 cites W4256462051 @default.
- W3097192014 doi "https://doi.org/10.1016/j.neucom.2020.10.054" @default.
- W3097192014 hasPublicationYear "2021" @default.
- W3097192014 type Work @default.
- W3097192014 sameAs 3097192014 @default.
- W3097192014 citedByCount "41" @default.
- W3097192014 countsByYear W30971920142021 @default.
- W3097192014 countsByYear W30971920142022 @default.
- W3097192014 countsByYear W30971920142023 @default.
- W3097192014 crossrefType "journal-article" @default.
- W3097192014 hasAuthorship W3097192014A5008919430 @default.
- W3097192014 hasAuthorship W3097192014A5013466530 @default.
- W3097192014 hasAuthorship W3097192014A5013795174 @default.
- W3097192014 hasAuthorship W3097192014A5074663989 @default.
- W3097192014 hasAuthorship W3097192014A5081650208 @default.
- W3097192014 hasConcept C102379954 @default.
- W3097192014 hasConcept C111919701 @default.
- W3097192014 hasConcept C119857082 @default.
- W3097192014 hasConcept C154945302 @default.
- W3097192014 hasConcept C2778579508 @default.
- W3097192014 hasConcept C2989133298 @default.
- W3097192014 hasConcept C38652104 @default.
- W3097192014 hasConcept C41008148 @default.
- W3097192014 hasConcept C541664917 @default.
- W3097192014 hasConcept C557433098 @default.
- W3097192014 hasConceptScore W3097192014C102379954 @default.
- W3097192014 hasConceptScore W3097192014C111919701 @default.
- W3097192014 hasConceptScore W3097192014C119857082 @default.
- W3097192014 hasConceptScore W3097192014C154945302 @default.
- W3097192014 hasConceptScore W3097192014C2778579508 @default.
- W3097192014 hasConceptScore W3097192014C2989133298 @default.
- W3097192014 hasConceptScore W3097192014C38652104 @default.
- W3097192014 hasConceptScore W3097192014C41008148 @default.
- W3097192014 hasConceptScore W3097192014C541664917 @default.
- W3097192014 hasConceptScore W3097192014C557433098 @default.
- W3097192014 hasFunder F4320321001 @default.
- W3097192014 hasLocation W30971920141 @default.
- W3097192014 hasOpenAccess W3097192014 @default.
- W3097192014 hasPrimaryLocation W30971920141 @default.
- W3097192014 hasRelatedWork W2092942461 @default.
- W3097192014 hasRelatedWork W2887046487 @default.
- W3097192014 hasRelatedWork W2890110856 @default.
- W3097192014 hasRelatedWork W2915981028 @default.
- W3097192014 hasRelatedWork W2945007260 @default.
- W3097192014 hasRelatedWork W2972851161 @default.
- W3097192014 hasRelatedWork W2980139868 @default.
- W3097192014 hasRelatedWork W3164409774 @default.
- W3097192014 hasRelatedWork W4210285013 @default.
- W3097192014 hasRelatedWork W4225165373 @default.
- W3097192014 hasVolume "423" @default.
- W3097192014 isParatext "false" @default.
- W3097192014 isRetracted "false" @default.
- W3097192014 magId "3097192014" @default.
- W3097192014 workType "article" @default.