TIF applies temporal invariant learning to Android malware detectors, improving F1 by up to 8 points in the first year after deployment across multiple feature spaces.
Recent advances in concept drift adaptation methods for deep learning,
1 Pith paper cite this work, alongside 3 external citations. Polarity classification is still indexing.
1
Pith paper citing it
3
external citations · OpenAlex
citation-role summary
background 1
citation-polarity summary
fields
cs.CR 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
TIF: Learning Temporal Invariance in Android Malware Detectors
TIF applies temporal invariant learning to Android malware detectors, improving F1 by up to 8 points in the first year after deployment across multiple feature spaces.