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Detecting covert communication on Android

Authors: Michael Hansen; Raquel Hill; Seth Wimberly;

Detecting covert communication on Android

Abstract

Using covert channels, malicious applications on Android-based smartphones are able to subvert the permission system and share data in a potentially untraceable manner. These channels are easy to exploit today, and have enough bandwidth to transmit sensitive information in real-time between collaborating applications. In this paper, we define and implement an application layer covert communications detector that does not require special permission from the user. We quantify the effect our detector has on channel capacities for malicious applications that wish to remain stealthy. Lastly, we evaluate the robustness of the volume and vibration channels on the Android emulator, HTC G1, and Motorola Droid, as well as characterize the effects of background noise on data loss and transfer rates.

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
8
Average
Top 10%
Top 10%
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