SDAC: A slow-aging solution for Android malware detection using semantic distance based API clustering
A novel slow-aging solution named SDAC is proposed to address the model aging problem in Android malware detection, which is due to the lack of adapting to the changes in Android specifications during malware detection. Different from periodic retraining of detection models in existing solutions, SD...
Saved in:
Main Authors: | XU, Jiayun, LI, Yingjiu, DENG, Robert H., KE, Xu |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2022
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/5996 https://ink.library.smu.edu.sg/context/sis_research/article/6999/viewcontent/SDAC_av_2020.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Machine learning based approaches towards robust Android malware detection
by: XU, Jiayun
Published: (2021) -
ICCDetector: ICC-based malware detection on Android
by: KE, Xu, et al.
Published: (2016) -
Semantics-aware Android malware classification using weighted contextual API dependency graphs
by: ZHANG, Mu, et al.
Published: (2014) -
Advanced malware detection for android platform
by: XU, Ke
Published: (2018) -
A software environment for confining malicious android applications via resource virtualization
by: Li, X., et al.
Published: (2014)