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Crowdroid: Behavior-Based Malware Detection System for Android
| Citations: | 83 - 0 self |
BibTeX
@MISC{Burguera_crowdroid:behavior-based,
author = {Iker Burguera and Urko Zurutuza and Simin Nadjm-tehrani},
title = {Crowdroid: Behavior-Based Malware Detection System for Android},
year = {}
}
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Abstract
The sharp increase in the number of smartphones on the market, with the Android platform posed to becoming a market leader makes the need for malware analysis on this platform an urgent issue. In this paper we capitalize on earlier approaches for dynamic analysis of application behavior as a means for detecting malware in the Android platform. The detector is embedded in a overall framework for collection of traces from an unlimited number of real users based on crowdsourcing. Our framework has been demonstrated by analyzing the data collected in the central server using two types of data sets: those from artificial malware created for test purposes, and those from real malware found in the wild. The method is shown to be an effective means of isolating the malware and alerting the users of a downloaded malware. This shows the potential for avoiding the spreading of a detected malware to a larger community.
Keyphrases
behavior-based malware detection system android platform application behavior data set downloaded malware real malware overall framework dynamic analysis malware analysis sharp increase effective mean urgent issue real user central server unlimited number test purpose artificial malware market leader detected malware
