The Concept Drift Problem in Android Malware Detection and Its Solution
Joint Authors
Hu, Donghui
Ma, Zhongjin
Zhang, Xiaotian
Li, Peipei
Ye, Dengpan
Ling, Baohong
Source
Security and Communication Networks
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-09-18
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
Currently, the Android platform is the most popular mobile platform in the world and holds a dominant share in the mobile device market.
With the popularization of the Android platform, large numbers of Android malware programs have begun to emerge on the Internet, and the sophistication of these programs is developing rapidly.
While many studies have already investigated Android malware detection through machine learning and have achieved good results, most of these are based on static data sources and fail to consider the concept drift problem resulting from the rapid growth in the number of Android malware programs and normal Android applications, as well as rapid technological advancement in the Android environment.
To address this problem, this work proposes a solution based on an ensemble classifier.
This ensemble classifier is based on a streaming data-based Naive Bayes classifier.
Android malware has identifiable feature utilization tendencies.
On this basis, feature selection algorithm is introduced into the ensemble classifier, and a sliding window is maintained inside the ensemble classifier.
Based on the performance of the subclassifiers inside the sliding window, the ensemble classifier makes dynamic adjustments to address the concept drift problem in Android malware detection.
The experimental results from the proposed method demonstrate that it can effectively address the concept drift problem in Android malware detection in a streaming data environment.
American Psychological Association (APA)
Hu, Donghui& Ma, Zhongjin& Zhang, Xiaotian& Li, Peipei& Ye, Dengpan& Ling, Baohong. 2017. The Concept Drift Problem in Android Malware Detection and Its Solution. Security and Communication Networks،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1202950
Modern Language Association (MLA)
Hu, Donghui…[et al.]. The Concept Drift Problem in Android Malware Detection and Its Solution. Security and Communication Networks No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1202950
American Medical Association (AMA)
Hu, Donghui& Ma, Zhongjin& Zhang, Xiaotian& Li, Peipei& Ye, Dengpan& Ling, Baohong. The Concept Drift Problem in Android Malware Detection and Its Solution. Security and Communication Networks. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1202950
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202950