Experimental study with real-world data for android app security analysis using machine learning
Although Machine Learning (ML) based approaches have shown promise for Android
malware detection, a set of critical challenges remain unaddressed. Some of those …
malware detection, a set of critical challenges remain unaddressed. Some of those …
Empirical assessment of machine learning-based malware detectors for Android: Measuring the gap between in-the-lab and in-the-wild validation scenarios
To address the issue of malware detection through large sets of applications, researchers
have recently started to investigate the capabilities of machine-learning techniques for …
have recently started to investigate the capabilities of machine-learning techniques for …
Android mobile malware detection using machine learning: A systematic review
With the increasing use of mobile devices, malware attacks are rising, especially on Android
phones, which account for 72.2% of the total market share. Hackers try to attack …
phones, which account for 72.2% of the total market share. Hackers try to attack …
Towards a fair comparison and realistic evaluation framework of android malware detectors based on static analysis and machine learning
As in other cybersecurity areas, machine learning (ML) techniques have emerged as a
promising solution to detect Android malware. In this sense, many proposals employing a …
promising solution to detect Android malware. In this sense, many proposals employing a …
Data-driven android malware intelligence: a survey
Android has dominated the smartphone market and become the most popular mobile
operating system. This rapidly increasing market share of Android has contributed to the …
operating system. This rapidly increasing market share of Android has contributed to the …
A review of android malware detection approaches based on machine learning
K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are developing rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …
malware is also emerging in an endless stream. Many researchers have studied the …
On building machine learning pipelines for Android malware detection: a procedural survey of practices, challenges and opportunities
As the smartphone market leader, Android has been a prominent target for malware attacks.
The number of malicious applications (apps) identified for it has increased continually over …
The number of malicious applications (apps) identified for it has increased continually over …
Comparative evaluation of machine learning-based malware detection on android.
S Hahn, M Protsenko, T Müller - 2016 - dl.gi.de
The Android platform is known as the market leader for mobile devices, but it also has
gained much attention among malware authors in recent years. The widespread of malware …
gained much attention among malware authors in recent years. The widespread of malware …
Why an android app is classified as malware: Toward malware classification interpretation
Machine learning–(ML) based approach is considered as one of the most promising
techniques for Android malware detection and has achieved high accuracy by leveraging …
techniques for Android malware detection and has achieved high accuracy by leveraging …
Droidapiminer: Mining api-level features for robust malware detection in android
The increasing popularity of Android apps makes them the target of malware authors. To
defend against this severe increase of Android malwares and help users make a better …
defend against this severe increase of Android malwares and help users make a better …