DocumentCode
654154
Title
Diagnosing smartphone´s abnormal behavior through robust outlier detection methods
Author
El Attar, Ali ; Khatoun, Rida ; Lemercier, Marc
Author_Institution
ICD / ERA &STMR, Univ. of Technol. of Troyes (UTT), Troyes, France
fYear
2013
fDate
28-31 Oct. 2013
Firstpage
1
Lastpage
3
Abstract
Smartphones have become increasingly popular and nowadays with the using of 3G networks, the needs in terms of connectivity in a business environment are substantial. Malicious use of such devices is highly dangerous since users may be victims of such use. In this paper, we present two statistical methods (Minimum Covariance Determinant (MCD) and Minimum Volume Ellipsoid (MVE) used to detect abnormal smartphone´s applications. Initial experiments results prove the efficiency and the accuracy of the MVE and MCD in detecting abnormal smartphone´s applications.
Keywords
covariance analysis; smart phones; 3G networks; MCD; MVE; business environment; minimum covariance determinant; minimum volume ellipsoid; robust outlier detection methods; smart phone abnormal behavior diagnosis; statistical methods; Batteries; Covariance matrices; Ellipsoids; Malware; Robustness; Smart phones;
fLanguage
English
Publisher
ieee
Conference_Titel
Global Information Infrastructure Symposium, 2013
Conference_Location
Trento
Type
conf
DOI
10.1109/GIIS.2013.6684358
Filename
6684358
Link To Document