Android Malware Detection based on Factorization Machine
, 2018 With the increasing popularity of Android smart phones in recent years, the amount of Android malware is growing rapidly. Due to its great threat and damage to mobile phone users, Android malware detection has become increasingly important in cyber ...
Li, Chenglin
core +1 more source
Detection of Android Malware in the Internet of Things through the K-Nearest Neighbor Algorithm. [PDF]
Sensors (Basel), 2023 Babbar H +4 more
europepmc +1 more source
Android Malware and Normal permissions dataset
, 2018 This dataset contains 18,850 normal android application packages and 10,000 malware android packages which are used to identify the behaviour of malware application on permission they need at run ...
Arvind Mahindru (7006262)
core +1 more source
FedDroidMeter: A Privacy Risk Evaluator for FL-Based Android Malware Classification Systems. [PDF]
Entropy (Basel), 2023 Jiang C, Xia C, Liu Z, Wang T.
europepmc +1 more source
Automated Android Malware Detection Using User Feedback. [PDF]
Sensors (Basel), 2022 Duque J +4 more
europepmc +1 more source
A Modified ResNeXt for Android Malware Identification and Classification. [PDF]
Comput Intell Neurosci, 2022 Albahar MA, ElSayed MS, Jurcut A.
europepmc +1 more source
Androfim: few-shot android malware family detection based on image representation
CybersecurityAndroid malware is the major cyber threat to the popular Android platform which may influence millions of end users. To battle against the Android malware, a large number of machine learning methods either based on 1) traditional feature extraction using
Fan Zhou +4 more
doaj +1 more source
On the evaluation of android malware detectors against code-obfuscation techniques. [PDF]
PeerJ Comput Sci, 2022 Nawaz U, Aleem M, Lin JC.
europepmc +1 more source
Malware Detection Techniques in Android
, 2015 Mobile Phones have become an important need of today. The term mobile phone and smart phone are almost identical now-a-days. Smartphone market is booming with very high speed.
Amit Jain, Pallavi Kaushik
core
An Android Malware Detection Approach to Enhance Node Feature Differences in a Function Call Graph Based on GCNs. [PDF]
Sensors (Basel), 2023 Wu H, Luktarhan N, Tian G, Song Y.
europepmc +1 more source