Linear SVM-Based Android Malware Detection for Reliable IoT Services
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 i...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/594501 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832558277614895104 |
|---|---|
| author | Hyo-Sik Ham Hwan-Hee Kim Myung-Sup Kim Mi-Jung Choi |
| author_facet | Hyo-Sik Ham Hwan-Hee Kim Myung-Sup Kim Mi-Jung Choi |
| author_sort | Hyo-Sik Ham |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d607bd2d05ae4668af704531c4df0b0a |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-d607bd2d05ae4668af704531c4df0b0a2025-02-03T01:32:51ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/594501594501Linear SVM-Based Android Malware Detection for Reliable IoT ServicesHyo-Sik Ham0Hwan-Hee Kim1Myung-Sup Kim2Mi-Jung Choi3Department of Computer Science, Kangwon National University, 1 Kangwondaehak-gil, Gangwon-do 200-701, Republic of KoreaDepartment of Computer Science, Kangwon National University, 1 Kangwondaehak-gil, Gangwon-do 200-701, Republic of KoreaDepartment of Computer and Information Science, Korea University, 2511 Sejong-ro, Sejong-si 339-770, Republic of KoreaDepartment of Computer Science, Kangwon National University, 1 Kangwondaehak-gil, Gangwon-do 200-701, Republic of KoreaCurrent 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.http://dx.doi.org/10.1155/2014/594501 |
| spellingShingle | Hyo-Sik Ham Hwan-Hee Kim Myung-Sup Kim Mi-Jung Choi Linear SVM-Based Android Malware Detection for Reliable IoT Services Journal of Applied Mathematics |
| title | Linear SVM-Based Android Malware Detection for Reliable IoT Services |
| title_full | Linear SVM-Based Android Malware Detection for Reliable IoT Services |
| title_fullStr | Linear SVM-Based Android Malware Detection for Reliable IoT Services |
| title_full_unstemmed | Linear SVM-Based Android Malware Detection for Reliable IoT Services |
| title_short | Linear SVM-Based Android Malware Detection for Reliable IoT Services |
| title_sort | linear svm based android malware detection for reliable iot services |
| url | http://dx.doi.org/10.1155/2014/594501 |
| work_keys_str_mv | AT hyosikham linearsvmbasedandroidmalwaredetectionforreliableiotservices AT hwanheekim linearsvmbasedandroidmalwaredetectionforreliableiotservices AT myungsupkim linearsvmbasedandroidmalwaredetectionforreliableiotservices AT mijungchoi linearsvmbasedandroidmalwaredetectionforreliableiotservices |