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 …

The evolution of android malware and android analysis techniques

K Tam, A Feizollah, NB Anuar, R Salleh… - ACM Computing …, 2017 - dl.acm.org
With the integration of mobile devices into daily life, smartphones are privy to increasing
amounts of sensitive information. Sophisticated mobile malware, particularly Android …

Malware analysis in IoT & android systems with defensive mechanism

CS Yadav, J Singh, A Yadav, HS Pattanayak, R Kumar… - Electronics, 2022 - mdpi.com
The Internet of Things (IoT) and the Android operating system have made cutting-edge
technology accessible to the general public. These are affordable, easy-to-use, and open …

Droidcat: Effective android malware detection and categorization via app-level profiling

H Cai, N Meng, B Ryder, D Yao - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …

[PDF][PDF] Drebin: Effective and explainable detection of android malware in your pocket.

D Arp, M Spreitzenbarth, M Hubner, H Gascon… - Ndss, 2014 - media.telefonicatech.com
Malicious applications pose a threat to the security of the Android platform. The growing
amount and diversity of these applications render conventional defenses largely ineffective …

Effective android malware detection with a hybrid model based on deep autoencoder and convolutional neural network

W Wang, M Zhao, J Wang - Journal of Ambient Intelligence and …, 2019 - Springer
Android security incidents occurred frequently in recent years. To improve the accuracy and
efficiency of large-scale Android malware detection, in this work, we propose a hybrid model …

Android security: a survey of issues, malware penetration, and defenses

P Faruki, A Bharmal, V Laxmi… - … surveys & tutorials, 2014 - ieeexplore.ieee.org
Smartphones have become pervasive due to the availability of office applications, Internet,
games, vehicle guidance using location-based services apart from conventional services …

Mamadroid: Detecting android malware by building markov chains of behavioral models (extended version)

L Onwuzurike, E Mariconti, P Andriotis… - ACM Transactions on …, 2019 - dl.acm.org
As Android has become increasingly popular, so has malware targeting it, thus motivating
the research community to propose different detection techniques. However, the constant …

Mamadroid: Detecting android malware by building markov chains of behavioral models

E Mariconti, L Onwuzurike, P Andriotis… - arXiv preprint arXiv …, 2016 - arxiv.org
The rise in popularity of the Android platform has resulted in an explosion of malware threats
targeting it. As both Android malware and the operating system itself constantly evolve, it is …

Droidapiminer: Mining api-level features for robust malware detection in android

Y Aafer, W Du, H Yin - Security and Privacy in Communication Networks …, 2013 - Springer
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 …