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 …

A survey for user behavior analysis based on machine learning techniques: current models and applications

A G. Martín, A Fernández-Isabel, I Martín de Diego… - Applied …, 2021 - Springer
Significant research has been carried out in the field of User Behavior Analysis, focused on
understanding, modeling and predicting past, present and future behaviors of users …

A Survey on Android Malware Detection Techniques Using Supervised Machine Learning

S Altaha, A Aljughiman, S Gul - IEEE Access, 2024 - ieeexplore.ieee.org
Android's open-source nature has contributed to the platform's rapid growth and its
widespread adoption. However, this widespread adoption of the Android operating system …

ASAINT: A spy App identification system based on network traffic

M Conti, G Rigoni, F Toffalini - … of the 15th International Conference on …, 2020 - dl.acm.org
Spy app is a class of malware for mobile devices that allows an adversary to steal sensitive
information. Detecting spy apps is challenging because they do not rely on classic malware …

Behavior-based malware detection system approach for mobile security using machine learning

S Vanjire, M Lakshmi - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
In today's world, mobile security is critical not only for our society but also for each individual.
Today, everyone wants their own mobile device, which has resulted in a growth in the …

A formal method for description and decision of android apps behavior based on process algebra

D Liang, L Shen, Z Chen, C Ma, J Feng - IEEE Access, 2022 - ieeexplore.ieee.org
Android is the most popular mobile platform, and it has become a primary malware target.
Existing behavior-based Android malware detection methods suffer from false positive and …

MDTA: a new approach of supervised machine learning for android malware detection and threat attribution using behavioral reports

SS Vanjire, M Lakshmi - Mobile Computing and Sustainable Informatics …, 2022 - Springer
Android is liable to malware attacks because of its open architecture, massive user base,
and easy access to its code. The security investigation depends upon the dynamic analysis …

AMon: A monitoring multidimensional feature application to secure Android environments

JA Gómez-Hernández… - 2021 IEEE Security …, 2021 - ieeexplore.ieee.org
This work introduces a novel Android monitoring app named AMon. It is aimed at collecting
device related information from several sources: communications,/proc filesystem …

A Data Flow-Based Approach for Classification and Risk Estimation of Android Apps

MM Uddin, R Surendran, GR Gokul… - … Conference on Recent …, 2023 - ieeexplore.ieee.org
The growing prevalence of Android applications (apps) has sparked concerns over the
security of users' personal information. Of particular concern is the potential leakage of …

User profiling based on network application traffic monitoring

F Shaman - 2020 - pearl.plymouth.ac.uk
There is increasing interest in identifying users and behaviour profiling from network traffic
metadata for traffic engineering and security monitoring. However, user identification and …