A Malware Detection Scheme Based on Mining Format Information
Joint Authors
Bai, Jinrong
Wang, Junfeng
Zou, Guozhong
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations.
In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files.
Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance.
When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998.
We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware.
Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates.
American Psychological Association (APA)
Bai, Jinrong& Wang, Junfeng& Zou, Guozhong. 2014. A Malware Detection Scheme Based on Mining Format Information. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1048948
Modern Language Association (MLA)
Bai, Jinrong…[et al.]. A Malware Detection Scheme Based on Mining Format Information. The Scientific World Journal No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1048948
American Medical Association (AMA)
Bai, Jinrong& Wang, Junfeng& Zou, Guozhong. A Malware Detection Scheme Based on Mining Format Information. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1048948
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048948