In this paper, we propose a new method of active learn-ing for Android malware detection. Our goal is to reduce the amount of human analyst effort needed to achieve a fixed performance, …

In this paper, we conducted a systematic literature review to search and analyze how deep learning approaches have been applied in the context of malware defenses in the Android …

Recent years have witnessed the proliferation of learning-based Android malware detectors. These detectors can be categorized into three types, String-based, Image-based and Graph …

In this project, a malware detection system is proposed that extracts permission and intent features from APK files using the SISIK web tool to effectively identify and classify applications …

We present Apposcopy, a new semantics-based approach for identifying a prevalent class of Android malware that steals private user information.

Abstract—With Android’s widespread adoption as the leading mobile operating system, it has become a prominent target for malware attacks. Many of these attacks employ advanced …

In this paper, we propose a new method of active learn-ing for Android malware detection. Our goal is to reduce the amount of human analyst effort needed to achieve a fixed performance, …