Matches in SemOpenAlex for { <https://semopenalex.org/work/W4210432040> ?p ?o ?g. }
Showing items 1 to 52 of
52
with 100 items per page.
- W4210432040 abstract "<pre> The popularity of the Android Operating System in the smartphone market has given rise to lots of Android malware. To accurately detect these malware, many of the existing works use machine learning and deep learning-based methods, in which feature extraction methods were used to extract fixed-size feature vectors using the files present inside the Android Application Package (APK). Recently, Graph Convolutional Network (GCN) based methods applied on the Function Call Graph (FCG) extracted from the APK are gaining momentum in Android malware detection, as GCNs are effective at learning tasks on variable-sized graphs such as FCG, and FCG sufficiently captures the structure and behaviour of an APK. However, the FCG lacks information about callback methods as the Android Application Programming Interface (API) is event-driven. This paper proposes enhancing the FCG to eFCG (enhanced-FCG) using the callback information extracted using Android Framework Space Analysis to overcome this limitation. Further, we add permission - API method relationships to the eFCG. The eFCG is reduced using node contraction based on the classes to get R-eFCG (Reduced eFCG) to improve the generalisation ability of the Android malware detection model. The eFCG and R-eFCG are then given as the inputs to the Heterogeneous GCN models to determine whether the APK file from which they are extracted is malicious or not. To test the effectiveness of eFCG and R-eFCG, we conducted an ablation study by removing their various components. To determine the optimal neighbourhood size for GCN, we experimented with a varying number of GCN layers and found that the Android malware detection model using R-eFCG with all its components with four convolution layers achieved maximum accuracy of 96.28%.</pre>" @default.
- W4210432040 created "2022-02-08" @default.
- W4210432040 creator A5052329854 @default.
- W4210432040 creator A5054016512 @default.
- W4210432040 date "2021-08-02" @default.
- W4210432040 modified "2023-10-16" @default.
- W4210432040 title "Heterogeneous Graph Convolutional Networks for Android Malware Detection using Callback-Aware Caller-Callee Graphs" @default.
- W4210432040 doi "https://doi.org/10.36227/techrxiv.15072087.v1" @default.
- W4210432040 hasPublicationYear "2021" @default.
- W4210432040 type Work @default.
- W4210432040 citedByCount "0" @default.
- W4210432040 crossrefType "posted-content" @default.
- W4210432040 hasAuthorship W4210432040A5052329854 @default.
- W4210432040 hasAuthorship W4210432040A5054016512 @default.
- W4210432040 hasBestOaLocation W42104320401 @default.
- W4210432040 hasConcept C111919701 @default.
- W4210432040 hasConcept C119857082 @default.
- W4210432040 hasConcept C154945302 @default.
- W4210432040 hasConcept C199360897 @default.
- W4210432040 hasConcept C204495577 @default.
- W4210432040 hasConcept C2778579508 @default.
- W4210432040 hasConcept C2989133298 @default.
- W4210432040 hasConcept C41008148 @default.
- W4210432040 hasConcept C541664917 @default.
- W4210432040 hasConcept C557433098 @default.
- W4210432040 hasConceptScore W4210432040C111919701 @default.
- W4210432040 hasConceptScore W4210432040C119857082 @default.
- W4210432040 hasConceptScore W4210432040C154945302 @default.
- W4210432040 hasConceptScore W4210432040C199360897 @default.
- W4210432040 hasConceptScore W4210432040C204495577 @default.
- W4210432040 hasConceptScore W4210432040C2778579508 @default.
- W4210432040 hasConceptScore W4210432040C2989133298 @default.
- W4210432040 hasConceptScore W4210432040C41008148 @default.
- W4210432040 hasConceptScore W4210432040C541664917 @default.
- W4210432040 hasConceptScore W4210432040C557433098 @default.
- W4210432040 hasLocation W42104320401 @default.
- W4210432040 hasLocation W42104320402 @default.
- W4210432040 hasOpenAccess W4210432040 @default.
- W4210432040 hasPrimaryLocation W42104320401 @default.
- W4210432040 hasRelatedWork W11793293 @default.
- W4210432040 hasRelatedWork W1539027 @default.
- W4210432040 hasRelatedWork W4081608 @default.
- W4210432040 hasRelatedWork W482721 @default.
- W4210432040 hasRelatedWork W6586136 @default.
- W4210432040 hasRelatedWork W6736853 @default.
- W4210432040 hasRelatedWork W7469215 @default.
- W4210432040 hasRelatedWork W8714722 @default.
- W4210432040 hasRelatedWork W9657784 @default.
- W4210432040 hasRelatedWork W14484578 @default.
- W4210432040 isParatext "false" @default.
- W4210432040 isRetracted "false" @default.
- W4210432040 workType "article" @default.