Document Type
Article
Publication Date
3-5-2020
Publication Title
Array
Volume
6
Abstract
If a malware detector relies heavily on a feature that is obfuscated in a given malware sample, then the detector will likely fail to correctly classify the malware. In this research, we obfuscate selected features of known Android malware samples and determine whether these obfuscated samples can still be reliably detected. Using this approach, we discover which features are most significant for various sets of Android malware detectors, in effect, performing a black box analysis of these detectors. We find that there is a surprisingly high degree of variability among the key features used by popular malware detectors.
Recommended Citation
Guruswamy Nellaivadivelu, Fabio Di Troia, and Mark Stamp. "Black box analysis of android malware detectors" Array (2020). https://doi.org/10.1016/j.array.2020.100022
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
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