Android receives major attention from security practitioners and researchers due to the influx
number of malicious applications. For the past twelve years, Android malicious applications …

In this paper, we propose a novel android malware detection system that uses a deep
convolutional neural network (CNN). Malware classification is performed based on static …

Android is a free open-source operating system (OS), which allows an in-depth
understanding of its architecture. Therefore, many manufacturers are utilizing this OS to …

Malware detection is a growing problem particularly on the Android mobile platform due to
its increasing popularity and accessibility to numerous third party app markets. This has also …

Until 2017, Android smartphones occupied approximately 87% of the smartphone market.
The vast market also promotes the development of Android malware. Nowadays, the …

Android malware is a major cyber threat to the popular Android platform which may
influence millions of end users. To battle against Android malware, a large number of …

Malware threats are growing, while at the same time, concealment strategies are being used
to make them undetectable for current commercial antivirus. Android is one of the target …

Android malware has been on the rise in recent years due to the increasing popularity of
Android and the proliferation of third party application markets. Emerging Android malware …

Ensemble learning–the application of multiple learning models on the same task–is a
common technique in multiple domains. While employing multiple models enables reaching …

In this paper, we propose a statistical approach for smartphone malware detection. A set of
features such as hardware, permission, application components, filtered intents, opcodes …