In this paper, we propose An Android Behavior-Based Malware Detection Method using
Machine Learning. We improve an Android application sandbox, Droidbox, by inserting a …

Because of exponential growth in smart mobile devices, malware attacks on smart mobile
devices have been growing and pose serious threats to mobile device users. To address …

In order to detect the security of Android software which isn't installed efficiently and
accurately, this paper proposes a new malware detection method based on system calls …

This paper proposes a two-stage Android malware detection and classification mechanism
based on machine learning algorithm. In this paper, we use the static analysis method to …

Android smart phones have become more and more popular due to its increasing
functionalities, compatibility and convenience. More and more Android applications have …

Android, the fastest growing mobile operating system released in November 2007, boasts of
a staggering 1.4 billion active users. Android users are susceptible to malicious applications …

The Android smartphone, with its open source character and excellent performance, has
attracted many users. However, the convenience of the Android platform also has motivated …

This paper proposes a (new) method to detect malware in Android smartphones using API
(application programming interface) classes. We use machine learning to classify whether …

Malware detection techniques come in many different flavors, and cover different
effectiveness and efficiency trade-offs. This paper evaluates a number of machine learning …

With the rapid growth of Android applications and malware, it has become a challenge to
distinguish malware from a huge number of applications. The use of behavioral analytics is …