Semantics-aware android malware classification using weighted contextual api dependency graphs

M Zhang, Y Duan, H Yin, Z Zhao - … of the 2014 ACM SIGSAC conference …, 2014 - dl.acm.org
The drastic increase of Android malware has led to a strong interest in developing methods
to automate the malware analysis process. Existing automated Android malware detection …

Droidlegacy: Automated familial classification of android malware

L Deshotels, V Notani, A Lakhotia - Proceedings of ACM SIGPLAN on …, 2014 - dl.acm.org
We present an automated method for extracting familial signatures for Android malware, ie,
signatures that identify malware produced by piggybacking potentially different benign …

[HTML][HTML] On machine learning effectiveness for malware detection in Android OS using static analysis data

V Syrris, D Geneiatakis - Journal of Information Security and Applications, 2021 - Elsevier
Although various security mechanisms have been introduced in Android operating system in
order to enhance its robustness, sheer protection remains an open issue: malicious …

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 …

Machine learning aided Android malware classification

N Milosevic, A Dehghantanha, KKR Choo - Computers & Electrical …, 2017 - Elsevier
The widespread adoption of Android devices and their capability to access significant
private and confidential information have resulted in these devices being targeted by …

Android malware detection via (somewhat) robust irreversible feature transformations

Q Han, VS Subrahmanian… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
As the most widely used OS on earth, Android is heavily targeted by malicious hackers.
Though much work has been done on detecting Android malware, hackers are becoming …

Droidscribe: Classifying android malware based on runtime behavior

SK Dash, G Suarez-Tangil, S Khan… - 2016 IEEE Security …, 2016 - ieeexplore.ieee.org
The Android ecosystem has witnessed a surge in malware, which not only puts mobile
devices at risk but also increases the burden on malware analysts assessing and …

Evaluation of android malware detection based on system calls

M Dimjašević, S Atzeni, I Ugrina… - Proceedings of the 2016 …, 2016 - dl.acm.org
With Android being the most widespread mobile platform, protecting it against malicious
applications is essential. Android users typically install applications from large remote …

Detection of repackaged android malware with code-heterogeneity features

K Tian, D Yao, BG Ryder, G Tan… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
During repackaging, malware writers statically inject malcode and modify the control flow to
ensure its execution. Repackaged malware is difficult to detect by existing classification …

Andmfc: Android malware family classification framework

S Türker, AB Can - 2019 IEEE 30th International Symposium on …, 2019 - ieeexplore.ieee.org
As the popularity of Android mobile operating system grows, the number of malicious
software have increased extensively. Therefore, many research efforts have been done on …