MalPurifier combines diversified adversarial perturbations, protective noise injection, and a denoising autoencoder with dual loss to defend Android malware detectors, reporting over 90.91% robust accuracy against 37 evasion attacks on two datasets.
Mamadroid: Detecting android mal- ware by building markov chains of behavioral models (extended version)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CR 1years
2023 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks
MalPurifier combines diversified adversarial perturbations, protective noise injection, and a denoising autoencoder with dual loss to defend Android malware detectors, reporting over 90.91% robust accuracy against 37 evasion attacks on two datasets.