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MadDroid: malicious adware detection in Android using deep learning
Saeed Seraj
,
Michalis Pavlidis
, Marcello Trovati
,
Nikolaos Polatidis
School of Arch, Tech and Eng
Research output
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Contribution to journal
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Article
›
peer-review
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Keyphrases
Deep Learning
100%
Android
100%
Adware Detection
100%
Adware
100%
Malware
30%
Vulnerability
10%
Evaluation Metrics
10%
Classification Accuracy
10%
User Data
10%
Malware Detection
10%
Deep Learning Methods
10%
Android Mobile Application
10%
Family Classification
10%
Advertising Fraud
10%
Benign Application
10%
Evasive Malware
10%
Fraud Cost
10%
Static Features
10%
Optimized Convolutional Neural Network
10%
Computer Science
Malware
100%
Android
100%
Deep Learning Method
100%
Evaluation Metric
6%
User Data
6%
Malware Detection
6%
Convolutional Neural Network
6%
Smartphone App
6%
Benign Application
6%