Iot-based android malware detection using graph neural network with adversarial defense
Since the Internet of Things (IoT) is widely adopted using Android applications, detecting
malicious Android apps is essential. In recent years, Android graph-based deep learning …
malicious Android apps is essential. In recent years, Android graph-based deep learning …
GDroid: Android malware detection and classification with graph convolutional network
The dramatic increase in the number of malware poses a serious challenge to the Android
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
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; …
Detecting and categorizing Android malware with graph neural networks
Android is the most dominant operating system in the mobile ecosystem. As expected, this
trend did not go unnoticed by miscreants, and quickly enough, it became their favorite …
trend did not go unnoticed by miscreants, and quickly enough, it became their favorite …
Robust android malware detection system against adversarial attacks using q-learning
Since the inception of Andoroid OS, smartphones sales have been growing exponentially,
and today it enjoys the monopoly in the smartphone marketplace. The widespread adoption …
and today it enjoys the monopoly in the smartphone marketplace. The widespread adoption …
Android malware detection through generative adversarial networks
Mobile and cell devices have empowered end users to tweak their cell phones more than
ever and introduce applications just as we used to with personal computers. Android …
ever and introduce applications just as we used to with personal computers. Android …
αCyber: Enhancing Robustness of Android Malware Detection System against Adversarial Attacks on Heterogeneous Graph based Model
The explosive growth and increasing sophistication of Android malware call for new
defensive techniques that are capable of protecting mobile users against novel threats. To …
defensive techniques that are capable of protecting mobile users against novel threats. To …
Adversarial-example attacks toward android malware detection system
Recently, it was shown that the generative adversarial network (GAN) based adversarial-
example attacks could thoroughly defeat the existing Android malware detection systems …
example attacks could thoroughly defeat the existing Android malware detection systems …
[HTML][HTML] DroidEnemy: battling adversarial example attacks for Android malware detection
N Bala, A Ahmar, W Li, F Tovar, A Battu… - Digital communications …, 2022 - Elsevier
In recent years, we have witnessed a surge in mobile devices such as smartphones, tablets,
smart watches, etc., most of which are based on the Android operating system. However …
smart watches, etc., most of which are based on the Android operating system. However …
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 …