2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) 2022
DOI: 10.1109/hora55278.2022.9800057
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A Deep Learning Based Android Malware Detection System with Static Analysis

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Cited by 18 publications
(10 citation statements)
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“…It is worth noting that due to the growing popularity of deep learning, researchers have extensively started using neural network classifiers in their work. Neural networks [72]- [76] have been involved in more than 35% of the studies mentioned in our review. Apart from the ML/DL [20] SVM, Rotation Forest, PART, FT, Random Committee, RF.…”
Section: Boosting In Machine Learningmentioning
confidence: 99%
“…It is worth noting that due to the growing popularity of deep learning, researchers have extensively started using neural network classifiers in their work. Neural networks [72]- [76] have been involved in more than 35% of the studies mentioned in our review. Apart from the ML/DL [20] SVM, Rotation Forest, PART, FT, Random Committee, RF.…”
Section: Boosting In Machine Learningmentioning
confidence: 99%
“…Multilayer Perceptron (MLP) has a structure in which many neurons with non-linear activation functions in architectural terms are hierarchically connected to each other. It uses a learning system called back-propagation [10].…”
Section: Machine Learning Modelsmentioning
confidence: 99%
“…Generally, a malware detection system consists of some detection steps by applying static, dynamic or hybrid analysis technique. The first of these is the signature-based static analysis [6][7][8]10] in which the analysis is made before the application is executed in the device. On the other hand, the second one is the dynamic analysis technique [4,[6][7][8][9]11] in which the behaviour is monitored in an isolated environment after the application is run, and the last one is the hybrid analysis technique [4,[7][8][9] which is using both these analysis techniques.…”
Section: Introductionmentioning
confidence: 99%
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“…Identifying libraries, malicious infrastructures, or packaged files may be valuable. Static analyses have been used to identify many malware variants [9][10][11][12]. The benefits of a static analysis include its speed and not requiring a controlled environment to run harmful code.…”
Section: Static Analysismentioning
confidence: 99%