Computing Adaptive Feature Weights with PSO to Improve Android Malware Detection
Joint Authors
Zheng, Kangfeng
Xu, Yanping
Wu, Chunhua
Wang, Xu
Lu, Tianliang
Niu, Xinxin
Source
Security and Communication Networks
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-17
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Abstract EN
Android malware detection is a complex and crucial issue.
In this paper, we propose a malware detection model using a support vector machine (SVM) method based on feature weights that are computed by information gain (IG) and particle swarm optimization (PSO) algorithms.
The IG weights are evaluated based on the relevance between features and class labels, and the PSO weights are adaptively calculated to result in the best fitness (the performance of the SVM classification model).
Moreover, to overcome the defects of basic PSO, we propose a new adaptive inertia weight method called fitness-based and chaotic adaptive inertia weight-PSO (FCAIW-PSO) that improves on basic PSO and is based on the fitness and a chaotic term.
The goal is to assign suitable weights to the features to ensure the best Android malware detection performance.
The results of experiments indicate that the IG weights and PSO weights both improve the performance of SVM and that the performance of the PSO weights is better than that of the IG weights.
American Psychological Association (APA)
Xu, Yanping& Wu, Chunhua& Zheng, Kangfeng& Wang, Xu& Niu, Xinxin& Lu, Tianliang. 2017. Computing Adaptive Feature Weights with PSO to Improve Android Malware Detection. Security and Communication Networks،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1202860
Modern Language Association (MLA)
Xu, Yanping…[et al.]. Computing Adaptive Feature Weights with PSO to Improve Android Malware Detection. Security and Communication Networks No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1202860
American Medical Association (AMA)
Xu, Yanping& Wu, Chunhua& Zheng, Kangfeng& Wang, Xu& Niu, Xinxin& Lu, Tianliang. Computing Adaptive Feature Weights with PSO to Improve Android Malware Detection. Security and Communication Networks. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1202860
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202860