A systematic literature review of android malware detection using static analysis
Android malware has been in an increasing trend in recent years due to the pervasiveness
of Android operating system. Android malware is installed and run on the smartphones …
of Android operating system. Android malware is installed and run on the smartphones …
Deep learning for zero-day malware detection and classification: A survey
Zero-day malware is malware that has never been seen before or is so new that no anti-
malware software can catch it. This novelty and the lack of existing mitigation strategies …
malware software can catch it. This novelty and the lack of existing mitigation strategies …
GDroid: Android malware detection and classification with graph convolutional network
The dramatic increase in the number of malware poses a serious challenge to the Android
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
A novel deep framework for dynamic malware detection based on API sequence intrinsic features
Dynamic malware detection executes the software in a secured virtual environment and
monitors its run-time behavior. This technique widely uses API sequence analysis to identify …
monitors its run-time behavior. This technique widely uses API sequence analysis to identify …
Similarity-based Android malware detection using Hamming distance of static binary features
In this paper, we develop four malware detection methods using Hamming distance to find
similarity between samples which are first nearest neighbors (FNN), all nearest neighbors …
similarity between samples which are first nearest neighbors (FNN), all nearest neighbors …
A dynamic Windows malware detection and prediction method based on contextual understanding of API call sequence
E Amer, I Zelinka - Computers & Security, 2020 - Elsevier
Malware API call graph derived from API call sequences is considered as a representative
technique to understand the malware behavioral characteristics. However, it is troublesome …
technique to understand the malware behavioral characteristics. However, it is troublesome …
PermPair: Android Malware Detection Using Permission Pairs
The Android smartphones are highly prone to spreading the malware due to intrinsic
feebleness that permits an application to access the internal resources when the user grants …
feebleness that permits an application to access the internal resources when the user grants …
Multi-view deep learning for zero-day Android malware detection
Zero-day malware samples pose a considerable danger to users as implicitly there are no
documented defences for previously unseen, newly encountered behaviour. Malware …
documented defences for previously unseen, newly encountered behaviour. Malware …
JOWMDroid: Android malware detection based on feature weighting with joint optimization of weight-map** and classifier parameters
L Cai, Y Li, Z **ong - Computers & Security, 2021 - Elsevier
Android malware detection is an important problem that must be urgently studied and
solved. Machine learning-based methods first extract features from applications and then …
solved. Machine learning-based methods first extract features from applications and then …
DroidEncoder: Malware detection using auto-encoder based feature extractor and machine learning algorithms
Android Malware detection became a hot topic over the last several years. Although
considerable studies have been conducted utilizing machine learning-based methods, little …
considerable studies have been conducted utilizing machine learning-based methods, little …