Cross-device behavioral consistency: Benchmarking and implications for effective android malware detection
Most of the proposed solutions using dynamic features for Android malware detection collect and test their systems using a single and particular data collection device, either a real device or an emulator. The results obtained using these particular devices are then generalized to any Android platfo...
Main Authors: | Alejandro Guerra-Manzanares, Martin Välbe |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2022-09-01
|
Series: | Machine Learning with Applications |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827022000561 |
Similar Items
-
BENCHMARKING MACHINE LEARNING ALGORITHMS FOR ANDROID MALWARE DETECTION
by: Somayyeh Fallah, et al.
Published: (2019-12-01) -
GANG-MAM: GAN based enGine for Modifying Android Malware
by: Renjith G., et al.
Published: (2022-06-01) -
PAIRED: An Explainable Lightweight Android Malware Detection System
by: Mohammed M. Alani, et al.
Published: (2022-01-01) -
Android malware detection with MH-100K: An innovative dataset for advanced research
by: Hendrio Bragança, et al.
Published: (2023-12-01) -
Android Malware Category and Family Identification Using Parallel Machine Learning
by: Ahmed Hashem El Fiky, et al.
Published: (2022-07-01)