Title :
Identifying Smartphone Malware Using Data Mining Technology
Author :
Chiang, Hsiu-Sen ; Tsaur, Woei-Jiunn
Author_Institution :
Dept. of Inf. Manage., Nat. Taichung Inst. of Technol., Taichung, Taiwan
fDate :
July 31 2011-Aug. 4 2011
Abstract :
The growing popularity of mobile devices such as smartphones and handsets has made mobile devices a more attractive target for mobile malware. Thus, the role of an anti-malware detector for effectively detecting mobile malware is becoming extremely important. In our previous work, we focused on constructing an ontology-based behavioral analysis for mobile malware, which provides information about mobile malware for end users to help them use their mobile phones securely. In this paper, we extend our previous work by employing the proposed technique of ontology-based behavioral analysis to develop a detection method for smartphone malware. It is expected that this research will contribute to the development of detection methods for unknown smartphone malware in mobile environments.
Keywords :
data mining; invasive software; mobile handsets; ontologies (artificial intelligence); antimalware detector; data mining technology; mobile devices; mobile malware; ontology-based behavioral analysis; smartphone malware identification; Bluetooth; Cognition; Grippers; Malware; Mobile communication; Mobile handsets; Ontologies;
Conference_Titel :
Computer Communications and Networks (ICCCN), 2011 Proceedings of 20th International Conference on
Conference_Location :
Maui, HI
Print_ISBN :
978-1-4577-0637-0
DOI :
10.1109/ICCCN.2011.6005937