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Reviving Android Malware with DroidRide: And How Not To

Authors: Min Huang; Kai Bu; Hanlin Wang; Kaiwen Zhu;

Reviving Android Malware with DroidRide: And How Not To

Abstract

Malware has started grabbing its undeserved share long before the blossom of Android ecosystem. Injected with malware, malicious applications (apps) may threat users in various ways like financial charges and information stealing. When the severity of a deluge of malware was first noticed, malware detectors delivered unsatisfactory detection accuracy, which further degenerated upon simple transformation of malicious apps. Now years later, we are eager to re-examine the robustness of malware detectors. A surprisingly disappointed finding is that even known malicious apps can evade quite a few detectors. We also find that repackaging with extracted exploitable code instead of readily available malware samples can evade more signature-based detectors. Furthermore, we find Android OS features of Service and Broadcast exploitable to enable malicious apps stealthily active on phones. We implement all these findings through DroidRide, a framework toward making Android malware less catchable to detectors and more active on phones. Our prototype based on two example apps—AndroRAT and MIUI Notes—demonstrates DroidRide's effectiveness in malware evasion. Toward defending against DroidRide alike evasion, we further suggest feasible design enhancements of malware detectors and Android OS.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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