metaNet: Interpretable unknown mobile malware identification with a novel meta-features mining algorithm

Z Li, Z Zhao, R Zhang, H Lu, W Li, F Zhang, S Lu… - Computer Networks, 2024 - Elsevier
The continuous emergence of malware has threatened to the Android platform and user
privacy. With the evolution of the Android system and malware, it is challenging to design a …

Creating better ground truth to further understand Android malware: A large scale mining approach based on antivirus labels and malicious artifacts

M Hurier - 2019 - orbilu.uni.lu
Mobile applications are essential for interacting with technology and other people. With
more than 2 billion devices deployed all over the world, Android offers a thriving ecosystem …

Lightweight, obfuscation-resilient detection and family identification of android malware

J Garcia, M Hammad, S Malek - ACM Transactions on Software …, 2018 - dl.acm.org
The number of malicious Android apps is increasing rapidly. Android malware can damage
or alter other files or settings, install additional applications, and so on. To determine such …

[PDF][PDF] Obfuscation-resilient, efficient, and accurate detection and family identification of android malware

J Garcia, M Hammad, B Pedrood… - … of Computer Science …, 2015 - cs.gmu.edu
The number of Android malware apps are increasing very quickly. Simply detecting and
removing malware apps is insufficient, since they can damage or alter other files, data, or …

Android Malware Family Clustering Based on Multiple Features

X Chen, D Yu, X Cai, H Jiang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Familiar analysis for malware plays an important role in comprehending the diversity of
malicious behaviors and identifying the emerging security threats. Existing studies mainly …

Meta-Learning for Multi-Family Android Malware Classification

Y Li, D Yuan, T Zhang, H Cai, D Lo, C Gao… - ACM Transactions on …, 2024 - dl.acm.org
With the emergence of smartphones, Android has become a widely used mobile operating
system. However, it is vulnerable when encountering various types of attacks. Every day …

A hybrid approach for android malware detection and family classification

M Dhalaria, E Gandotra - 2020 - ir.juit.ac.in
With the increase in the popularity of mobile devices, malicious applications targeting
Android platform have greatly increased. Malware is coded so prudently that it has become …

Ec2: Ensemble clustering and classification for predicting android malware families

T Chakraborty, F Pierazzi… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
As the most widely used mobile platform, Android is also the biggest target for mobile
malware. Given the increasing number of Android malware variants, detecting malware …

Android Malware Family Classification: What Works–API Calls, Permissions or API Packages?

S Kumar, D Mishra, SK Shukla - 2021 14th International …, 2021 - ieeexplore.ieee.org
With the increased popularity and wide adoption of Android as a mobile OS platform, it has
been a major target for malware authors. Due to unprecedented rapid growth in the number …

Droidsieve: Fast and accurate classification of obfuscated android malware

G Suarez-Tangil, SK Dash, M Ahmadi… - Proceedings of the …, 2017 - dl.acm.org
With more than two million applications, Android marketplaces require automatic and
scalable methods to efficiently vet apps for the absence of malicious threats. Recent …