Android malware detection based on sensitive patterns

Kang Liu (), Guanghui Zhang (), Xue Chen (), Qing Liu (), Linyu Peng () and Liu Yurui ()
Additional contact information
Kang Liu: Power Dispatching Control Center of Guizhou Power Grid Co., Ltd
Guanghui Zhang: Power Dispatching Control Center of Guizhou Power Grid Co., Ltd
Xue Chen: University of Electronic Science and Technology of China
Qing Liu: Power Dispatching Control Center of Guizhou Power Grid Co., Ltd
Linyu Peng: Power Dispatching Control Center of Guizhou Power Grid Co., Ltd
Liu Yurui: Power Dispatching Control Center of Guizhou Power Grid Co., Ltd

Telecommunication Systems: Modelling, Analysis, Design and Management, 2023, vol. 82, issue 4, No 1, 435-449

Abstract: Abstract In recent years, the rapid increase in the number and type of Android malware has brought great challenges and pressure to malware detection systems. As a widely used method in android malware detection, static detecting has been a hot topic in academia and industry. However, in order to improve the accuracy of detection, the existing static detecting methods sacrifice the excessively high analysis complexity and time cost. Moreover, the correlation between static features leads to redundancy of a large amount of data. Therefore, this paper proposes a static detecting method of Android malware based on sensitive pattern. It uses an improved FP-growth algorithm to mine frequent combinations of sensitive permissions and API calls in malicious apps and benign apps, which avoids the generation of redundant information. In addition, this paper adopts multi-layered gradient boosting decision trees algorithm to train the detection model. And a dual similarity combination method is proposed to measure the similarity between different sensitive patterns. The experimental results show that our proposed detection method has high accuracy and great generalization ability.

Keywords: Android malware; Sensitive pattern; Static detecting (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11235-022-00983-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:telsys:v:82:y:2023:i:4:d:10.1007_s11235-022-00983-2

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/11235

DOI: 10.1007/s11235-022-00983-2

Access Statistics for this article

Telecommunication Systems: Modelling, Analysis, Design and Management is currently edited by Muhammad Khan

More articles in Telecommunication Systems: Modelling, Analysis, Design and Management from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().