A Graph-Based Feature Generation Approach in Android Malware Detection with Machine Learning Techniques

Xiaojian Liu, Qian Lei and Kehong Liu

Mathematical Problems in Engineering, 2020, vol. 2020, 1-15

Abstract:

An explosive spread of Android malware causes a serious concern for Android application security. One of the solutions to detecting malicious payloads sneaking in an application is to treat the detection as a binary classification problem, which can be effectively tackled with traditional machine learning techniques. The key factors in detecting Android malware with machine learning techniques are feature selection and generation . Most of the existing approaches select and generate features without fully examining the structures of programs, and thus the important semantic information associated with these features is lost, consequently resulting in a low accuracy rate in detection. To address this issue, we propose a new feature generation approach for Android applications, which takes components and program structures into consideration and extracts features in a graph-based and semantics-rich style. This approach highlights two major distinguishing aspects: the context-based feature selection and graph-based feature generation . We abstract an Android application as a collection of reduced iCFGs (interprocedural control flow graphs) and extract original features from these graphs. Combining the original features and their contexts together, we generate new features which hold richer semantic information than the original ones. By embedding the features into a feature vector space, we can use machine learning techniques to train a malware detector. The experiment results show that this approach achieves an accuracy rate of 95.4% and a recall rate of 96.5%, which prove the effectiveness and advantages of our approach.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2020/3842094.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2020/3842094.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3842094

DOI: 10.1155/2020/3842094

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().