[HTML][HTML] AdStop: Efficient flow-based mobile adware detection using machine learning
In recent years, mobile devices have become commonly used not only for voice
communications but also to play a major role in our daily activities. Accordingly, the number …
communications but also to play a major role in our daily activities. Accordingly, the number …
A mobile malware detection method using behavior features in network traffic
Android has become the most popular mobile platform due to its openness and flexibility.
Meanwhile, it has also become the main target of massive mobile malware. This …
Meanwhile, it has also become the main target of massive mobile malware. This …
MAPAS: a practical deep learning-based android malware detection system
A lot of malicious applications appears every day, threatening numerous users. Therefore, a
surge of studies have been conducted to protect users from newly emerging malware by …
surge of studies have been conducted to protect users from newly emerging malware by …
An analysis of Android adware
Most Android smartphone applications, or apps, are free—to generate revenue,
advertisements are displayed when an app is used. Billions of dollars are lost annually due …
advertisements are displayed when an app is used. Billions of dollars are lost annually due …
A two-layer deep learning method for android malware detection using network traffic
J Feng, L Shen, Z Chen, Y Wang, H Li - Ieee Access, 2020 - ieeexplore.ieee.org
Because of the characteristic of openness and flexibility, Android has become the most
popular mobile platform. However, it has also become the most targeted system by mobile …
popular mobile platform. However, it has also become the most targeted system by mobile …
Detecting android malware leveraging text semantics of network flows
The emergence of malicious apps poses a serious threat to the Android platform. Most types
of mobile malware rely on network interface to coordinate operations, steal users' private …
of mobile malware rely on network interface to coordinate operations, steal users' private …
Self-attention based convolutional-LSTM for android malware detection using network traffics grayscale image
L Shen, J Feng, Z Chen, Z Sun, D Liang, H Li… - Applied Intelligence, 2023 - Springer
To accurately find malware in a large number of mobile APPs, and determine which family it
belongs to is one of the most important challenges in Android malware detection. Existed …
belongs to is one of the most important challenges in Android malware detection. Existed …
An early detection of android malware using system calls based machine learning model
Several host intrusion detection systems (HIDSs) based on system call analysis have been
proposed in the past to detect intrusions and malware using relevant datasets. Machine …
proposed in the past to detect intrusions and malware using relevant datasets. Machine …
A survey on mobile malware detection methods using machine learning
The prevalence of mobile devices (smartphones) along with the availability of high-speed
internet access world-wide resulted in a wide variety of mobile applications that carry a large …
internet access world-wide resulted in a wide variety of mobile applications that carry a large …
[PDF][PDF] RobotDroid: a lightweight malware detection framework on smartphones
M Zhao, T Zhang, F Ge, Z Yuan - Journal of Networks, 2012 - Citeseer
Smartphones have been widely used in recent years due to their capabilities of
communication and multimedia processing, thus they also become attack targets of …
communication and multimedia processing, thus they also become attack targets of …