SeGDroid: An Android malware detection method based on sensitive function call graph learning
Malware is still a challenging security problem in the Android ecosystem, as malware is
often obfuscated to evade detection. In such case, semantic behavior feature extraction is …
often obfuscated to evade detection. In such case, semantic behavior feature extraction is …
Android malware detection via graph representation learning
With the widespread usage of Android smartphones in our daily lives, the Android platform
has become an attractive target for malware authors. There is an urgent need for developing …
has become an attractive target for malware authors. There is an urgent need for developing …
Android malware detection based on call graph via graph neural network
With the widespread usage of Android smart-phones in our daily lives, Android platform has
become an attractive target for malware authors. There is an urgent need for developing …
become an attractive target for malware authors. There is an urgent need for developing …
Learning features from enhanced function call graphs for Android malware detection
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 …
paper, we attempt to learn the behavior level features of an app from function calls. The …
Out-of-sample node representation learning for heterogeneous graph in real-time android malware detection
The increasingly sophisticated Android malware calls for new defensive techniques that are
capable of protecting mobile users against novel threats. In this paper, we first extract the …
capable of protecting mobile users against novel threats. In this paper, we first extract the …
Android malware detection using function call graph with graph convolutional networks
KV Vinayaka, CD Jaidhar - 2021 2nd International Conference …, 2021 - ieeexplore.ieee.org
As smartphone adoption is happening at a rapid rate, its threat landscape is also widening.
Android is a popular smartphone Operating System (OS) which was subject to many …
Android is a popular smartphone Operating System (OS) which was subject to many …
AMDroid: android malware detection using function call graphs
With the rapid development of the mobile Internet, Android has been the most popular
mobile operating system. Due to the open nature of Android, c countless malicious …
mobile operating system. Due to the open nature of Android, c countless malicious …
Graph convolutional networks for android malware detection with system call graphs
Nowadays, Android malwares have risen precipitously causing critical security threats.
Malware authors now employ a variety of obfuscation techniques to evade their detection …
Malware authors now employ a variety of obfuscation techniques to evade their detection …
AMalNet: A deep learning framework based on graph convolutional networks for malware detection
X Pei, L Yu, S Tian - Computers & Security, 2020 - Elsevier
The increasing popularity of Android apps attracted widespread attention from malware
authors. Traditional malware detection systems suffer from some shortcomings; …
authors. Traditional malware detection systems suffer from some shortcomings; …
[HTML][HTML] OpCode-level function call graph based android malware classification using deep learning
W Niu, R Cao, X Zhang, K Ding, K Zhang, T Li - Sensors, 2020 - mdpi.com
Due to the openness of an Android system, many Internet of Things (IoT) devices are
running the Android system and Android devices have become a common control terminal …
running the Android system and Android devices have become a common control terminal …