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Crowdroid: Behavior-Based Malware Detection Systemfor Android
Electronics and Computing Department, Mondragon University.
Electronics and Computing Department, Mondragon University.
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology. (Real-time Systems Laboratory)
2011 (English)Conference paper (Refereed)
Abstract [en]

The sharp increase in the number of smartphones on themarket, with the Android platform posed to becoming amarket leader makes the need for malware analysis on thisplatform an urgent issue.In this paper we capitalize on earlier approaches for dynamicanalysis of application behavior as a means for detectingmalware in the Android platform. The detector is embeddedin a overall framework for collection of traces from anunlimited number of real users based on crowdsourcing. Ourframework has been demonstrated by analyzing the datacollected in the central server using two types of data sets:those from articial malware created for test purposes, andthose from real malware found in the wild. The method isshown to be an eective means of isolating the malware andalerting the users of a downloaded malware. This shows thepotential for avoiding the spreading of a detected malwareto a larger community.

Place, publisher, year, edition, pages
ACM , 2011.
Keyword [en]
Security, Experimentation
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-72358DOI: 10.1145/2046614.2046619OAI: diva2:460322
Workshop on Security and Privacy in Smartphones and Mobile Devices, SPSM
Available from: 2011-12-16 Created: 2011-11-25 Last updated: 2011-12-16Bibliographically approved

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Nadjm-Tehrani, Simin
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Department of Computer and Information ScienceThe Institute of Technology
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ReferencesLink to record
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