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  4. Malware detection on mobile devices using distributed machine learning
 
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2010
Konferenzbeitrag
Titel

Malware detection on mobile devices using distributed machine learning

Abstract
This paper presents a distributed Support Vector Machine (SVM) algorithm in order to detect malicious software (malware) on a network of mobile devices. The light-weight system monitors mobile user activity in a distributed and privacy-preserving way using a statistical classification model which is evolved by training with examples of both normal usage patterns and unusual behavior. The system is evaluated using the MIT reality mining data set. The results indicate that the distributed learning system trains quickly and performs reliably. Moreover, it is robust against failures of individual components.
Author(s)
Sharifi Shamili, A.
Bauckhage, C.
Alpcan, T.
Hauptwerk
ICPR 2010, 20th International Conference on Pattern Recognition. Proceedings
Konferenz
International Conference on Pattern Recognition (ICPR) 2010
DOI
10.1109/ICPR.2010.1057
File(s)
002.pdf (446.27 KB)
Language
Englisch
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