Detecting SMS-based control commands in a Botnet from infected android devices

Nguyen, Anh and Pan, Lei 2012, Detecting SMS-based control commands in a Botnet from infected android devices, in ATIS 2012 : Proceedings of the 3rd Applications and Technologies in Information Security Workshop, School of Information Systems, Deakin University, Melbourne, Vic., pp. 23-27.

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Title Detecting SMS-based control commands in a Botnet from infected android devices
Author(s) Nguyen, Anh
Pan, Lei
Conference name Applications and Technologies in Information Security. Workshop (3rd : 2012 : Melbourne, Vic.)
Conference location Melbourne, Vic.
Conference dates 7 Nov. 2012
Title of proceedings ATIS 2012 : Proceedings of the 3rd Applications and Technologies in Information Security Workshop
Editor(s) Warren, Matthew
Publication date 2012
Conference series Applications and Technologies in Information Security Workshop
Start page 23
End page 27
Total pages 5
Publisher School of Information Systems, Deakin University
Place of publication Melbourne, Vic.
Keyword(s) botnet
logging
android
digital forensics
Summary An increasing number of Android devices are being infected and at risk of becoming part of a botnet. Among all types of botnets, control and cornmand based botnets are very popular. In this paper we introduce an effective and efficient method to ddect SMS-based control commands ftvm infected Android devices. Specifically, we rely on the important radio activities recorded in Android log files. These radio activities are currently overlooked by researchers. We show the effectiveness of our rnethod by using the examples frorn published literature. Our method requires much less user knowledge but is more generic than traditional approaches.
ISBN 9780987229823
Language eng
Field of Research 080303 Computer System Security
080499 Data Format not elsewhere classified
Socio Economic Objective 890202 Application Tools and System Utilities
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30051357

Document type: Conference Paper
Collection: School of Information Technology
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