Detecting Android Malwares with High-Efficient Hybrid Analyzing Methods
Joint Authors
Liu, Yu
Huang, Xiangdong
Guo, Kai
Zhou, Zhou
Zhang, Yichi
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-13
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Telecommunications Engineering
Abstract EN
In order to tackle the security issues caused by malwares of Android OS, we proposed a high-efficient hybrid-detecting scheme for Android malwares.
Our scheme employed different analyzing methods (static and dynamic methods) to construct a flexible detecting scheme.
In this paper, we proposed some detecting techniques such as Com+ feature based on traditional Permission and API call features to improve the performance of static detection.
The collapsing issue of traditional function call graph-based malware detection was also avoided, as we adopted feature selection and clustering method to unify function call graph features of various dimensions into same dimension.
In order to verify the performance of our scheme, we built an open-access malware dataset in our experiments.
The experimental results showed that the suggested scheme achieved high malware-detecting accuracy, and the scheme could be used to establish Android malware-detecting cloud services, which can automatically adopt high-efficiency analyzing methods according to the properties of the Android applications.
American Psychological Association (APA)
Liu, Yu& Guo, Kai& Huang, Xiangdong& Zhou, Zhou& Zhang, Yichi. 2018. Detecting Android Malwares with High-Efficient Hybrid Analyzing Methods. Mobile Information Systems،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1204671
Modern Language Association (MLA)
Liu, Yu…[et al.]. Detecting Android Malwares with High-Efficient Hybrid Analyzing Methods. Mobile Information Systems No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1204671
American Medical Association (AMA)
Liu, Yu& Guo, Kai& Huang, Xiangdong& Zhou, Zhou& Zhang, Yichi. Detecting Android Malwares with High-Efficient Hybrid Analyzing Methods. Mobile Information Systems. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1204671
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1204671