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Mlifdect: Android Malware Detection Based on Parallel Machine Learning and Information Fusion
Joint Authors
Zhang, Dafang
Su, Xin
Wang, Xin
Li, Wenjia
Source
Security and Communication Networks
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-28
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Abstract EN
In recent years, Android malware has continued to grow at an alarming rate.
More recent malicious apps’ employing highly sophisticated detection avoidance techniques makes the traditional machine learning based malware detection methods far less effective.
More specifically, they cannot cope with various types of Android malware and have limitation in detection by utilizing a single classification algorithm.
To address this limitation, we propose a novel approach in this paper that leverages parallel machine learning and information fusion techniques for better Android malware detection, which is named Mlifdect.
To implement this approach, we first extract eight types of features from static analysis on Android apps and build two kinds of feature sets after feature selection.
Then, a parallel machine learning detection model is developed for speeding up the process of classification.
Finally, we investigate the probability analysis based and Dempster-Shafer theory based information fusion approaches which can effectively obtain the detection results.
To validate our method, other state-of-the-art detection works are selected for comparison with real-world Android apps.
The experimental results demonstrate that Mlifdect is capable of achieving higher detection accuracy as well as a remarkable run-time efficiency compared to the existing malware detection solutions.
American Psychological Association (APA)
Wang, Xin& Zhang, Dafang& Su, Xin& Li, Wenjia. 2017. Mlifdect: Android Malware Detection Based on Parallel Machine Learning and Information Fusion. Security and Communication Networks،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1203054
Modern Language Association (MLA)
Wang, Xin…[et al.]. Mlifdect: Android Malware Detection Based on Parallel Machine Learning and Information Fusion. Security and Communication Networks No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1203054
American Medical Association (AMA)
Wang, Xin& Zhang, Dafang& Su, Xin& Li, Wenjia. Mlifdect: Android Malware Detection Based on Parallel Machine Learning and Information Fusion. Security and Communication Networks. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1203054
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1203054