Linear SVM-Based Android Malware Detection for Reliable IoT Services
Joint Authors
Ham, Hyo-Sik
Kim, Hwan-Hee
Kim, Myung-Sup
Choi, Mi-Jung
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-09-03
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Current many Internet of Things (IoT) services are monitored and controlled through smartphone applications.
By combining IoT with smartphones, many convenient IoT services have been provided to users.
However, there are adverse underlying effects in such services including invasion of privacy and information leakage.
In most cases, mobile devices have become cluttered with important personal user information as various services and contents are provided through them.
Accordingly, attackers are expanding the scope of their attacks beyond the existing PC and Internet environment into mobile devices.
In this paper, we apply a linear support vector machine (SVM) to detect Android malware and compare the malware detection performance of SVM with that of other machine learning classifiers.
Through experimental validation, we show that the SVM outperforms other machine learning classifiers.
American Psychological Association (APA)
Ham, Hyo-Sik& Kim, Hwan-Hee& Kim, Myung-Sup& Choi, Mi-Jung. 2014. Linear SVM-Based Android Malware Detection for Reliable IoT Services. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1039745
Modern Language Association (MLA)
Ham, Hyo-Sik…[et al.]. Linear SVM-Based Android Malware Detection for Reliable IoT Services. Journal of Applied Mathematics No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1039745
American Medical Association (AMA)
Ham, Hyo-Sik& Kim, Hwan-Hee& Kim, Myung-Sup& Choi, Mi-Jung. Linear SVM-Based Android Malware Detection for Reliable IoT Services. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1039745
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1039745