Dec 16, 2020 · The purpose of this paper is to achieve multiclassification of Android malware; therefore, the output of our system is the malicious family ...
Jan 22, 2021 · This paper uses three classes of Android App APK features: classes.dex file, class name collection and API call sequence as input for App visualization.
In this paper, a method of color visualization for Android Apps is proposed and implemented. Based on this, combined with deep learning models, a multi- ...
A Multi-class Detection System for Android Malicious Apps Based on Color Image Features ... image‐based android malware detection and variant classification.
People also ask
How do I find hidden malware apps on my Android?
What is BFEDroid a feature selection technique to detect malware in Android apps using machine learning?
How do I get rid of malicious apps on Android?
How do I know if malicious app is installed?
In 2018, TonTon Hsien-De Huang and Hung-Yu Kao [4] proposed a color-inspired Convolutional Neural Network. (CNN) method for detecting Android malware. This ...
Missing: Apps | Show results with:Apps
Gao, A multi-class detection system for Android malicious apps based on color image features, International Conference on Security and Privacy in New ...
AMD-CNN [8] is an Android malware detection tool. It works by extracting features from the AndroidManifest.xml file and converting them to images feeding a CNN ...
Jun 29, 2020 · In this paper, a malware classification model has been proposed for detecting malware samples in the Android environment.
Aug 18, 2023 · Deeprefiner: Multi-layer android malware detection system ... A multi-class detection system for android malicious apps based on color image ...
The proposed technique employs two image descriptors, GIST and HOG, to analyze memory dump images and identify malicious and benign programs.
Missing: Apps | Show results with:Apps