Malicious application detection in android—a systematic literature review

T Sharma, D Rattan - Computer Science Review, 2021 - Elsevier
Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …

Intelligent mobile malware detection using permission requests and API calls

M Alazab, M Alazab, A Shalaginov, A Mesleh… - Future Generation …, 2020 - Elsevier
Malware is a serious threat that has been used to target mobile devices since its inception.
Two types of mobile malware attacks are standalone: fraudulent mobile apps and injected …

[Retracted] A Comprehensive Review of Android Security: Threats, Vulnerabilities, Malware Detection, and Analysis

S Acharya, U Rawat… - Security and …, 2022 - Wiley Online Library
The popularity and open‐source nature of Android devices have resulted in a dramatic
growth of Android malware. Malware developers are also able to evade the detection …

Hindroid: An intelligent android malware detection system based on structured heterogeneous information network

S Hou, Y Ye, Y Song, M Abdulhayoglu - Proceedings of the 23rd ACM …, 2017 - dl.acm.org
With explosive growth of Android malware and due to the severity of its damages to smart
phone users, the detection of Android malware has become increasingly important in …

Android malware detection based on system call sequences and LSTM

X Xiao, S Zhang, F Mercaldo, G Hu… - Multimedia Tools and …, 2019 - Springer
As Android-based mobile devices become increasingly popular, malware detection on
Android is very crucial nowadays. In this paper, a novel detection method based on deep …

A novel dynamic android malware detection system with ensemble learning

P Feng, J Ma, C Sun, X Xu, Y Ma - IEEE Access, 2018 - ieeexplore.ieee.org
With the popularity of Android smartphones, malicious applications targeted Android
platform have explosively increased. Proposing effective Android malware detection method …

Deep4maldroid: A deep learning framework for android malware detection based on linux kernel system call graphs

S Hou, A Saas, L Chen, Y Ye - 2016 IEEE/WIC/ACM …, 2016 - ieeexplore.ieee.org
With explosive growth of Android malware and due to its damage to smart phone users (eg,
stealing user credentials, resource abuse), Android malware detection is one of the cyber …

Deep learning for effective Android malware detection using API call graph embeddings

A Pektaş, T Acarman - Soft Computing, 2020 - Springer
High penetration of Android applications along with their malicious variants requires efficient
and effective malware detection methods to build mobile platform security. API call …

Robust deep learning early alarm prediction model based on the behavioural smell for android malware

E Amer, S El-Sappagh - Computers & Security, 2022 - Elsevier
Due to the widespread expansion of the Android malware industry, malicious Android
processes mining became a necessity to understand their behavior. Nevertheless, due to …

A TAN based hybrid model for android malware detection

R Surendran, T Thomas, S Emmanuel - Journal of Information Security and …, 2020 - Elsevier
Android devices are very popular because of their availability at reasonable prices.
However, there is a rapid rise of malware applications in Android platform in the recent past …