Android security assessment: A review, taxonomy and research gap study

S Garg, N Baliyan - Computers & Security, 2021 - Elsevier
Security threats are escalating exponentially posing a serious challenge to mobile platforms,
specifically Android. In recent years the number of attacks has not only increased but each …

A survey of recent advances in deep learning models for detecting malware in desktop and mobile platforms

P Maniriho, AN Mahmood, MJM Chowdhury - ACM Computing Surveys, 2024 - dl.acm.org
Malware is one of the most common and severe cyber threats today. Malware infects
millions of devices and can perform several malicious activities including compromising …

SeGDroid: An Android malware detection method based on sensitive function call graph learning

Z Liu, R Wang, N Japkowicz, HM Gomes… - Expert Systems with …, 2024 - Elsevier
Malware is still a challenging security problem in the Android ecosystem, as malware is
often obfuscated to evade detection. In such case, semantic behavior feature extraction is …

Uncovering and exploiting hidden apis in mobile super apps

C Wang, Y Zhang, Z Lin - Proceedings of the 2023 ACM SIGSAC …, 2023 - dl.acm.org
Mobile applications, particularly those from social media platforms such as WeChat and
TikTok, are evolving into" super apps" that offer a wide range of services such as instant …

Hierarchical bidirectional RNN for safety-enhanced B5G heterogeneous networks

Y Xu, X Yan, Y Wu, Y Hu, W Liang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The emergence of the beyond 5G (B5G) mobile networks has provided us with a variety of
services and enriched our lives. The B5G super-heterogeneous network systems and highly …

Voicify Your UI: Towards Android App Control with Voice Commands

MD Vu, H Wang, Z Li, G Haffari, Z **ng… - Proceedings of the ACM …, 2023 - dl.acm.org
Nowadays, voice assistants help users complete tasks on the smartphone with voice
commands, replacing traditional touchscreen interactions when such interactions are …

Obfuscation detection in android applications using deep learning

M Conti, P Vinod, A Vitella - Journal of Information Security and …, 2022 - Elsevier
Malware is often hidden in illegitimately cloned software. Android, with over two billions
active devices, is one of the most affected platforms because code cloning is quite simple …

Taming reflection: An essential step toward whole-program analysis of android apps

X Sun, L Li, TF Bissyandé, J Klein, D Octeau… - ACM Transactions on …, 2021 - dl.acm.org
Android developers heavily use reflection in their apps for legitimate reasons. However,
reflection is also significantly used for hiding malicious actions. Unfortunately, current state …

PrivacyGuard: Exploring Hidden Cross-App Privacy Leakage Threats In IoT Apps

Z Wang, B Luo, F Li - Proceedings on Privacy Enhancing …, 2025 - petsymposium.org
The increasing use of the Internet of Things (IoT) technology has made our lives convenient,
however, it also poses new security and privacy threats. In this work, we study a new type of …

Behaviour analysis of inter-app communication using a lightweight monitoring app for malware detection

M Grace, M Sughasiny - Expert Systems with Applications, 2022 - Elsevier
Smartphone communications are becoming more and more useful for businesses to plan
and organize their work and are mainly operated with android applications. The …