Android Malware Detection Method Based on Permission Complement and API Calls

Author:

YANG Jiyun1,TANG Jiang1,YAN Ran1,XIANG Tao1

Affiliation:

1. College of Computer ScienceChongqing UniversityChongqing400044China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering

Reference32 articles.

1. IDC “Smartphone market share ” available at:http://www.idc.com/prodserv/smartphone‐os‐market‐share.jsp 2020.

2. Forbes “Many popular android apps leak sensitive data leaving millions of consumers at risk ” available at:https://www.forbes.com/sites/ajdellinger/2019/06/07/many‐popularandroid‐apps‐leak‐sensitive‐data‐leaving‐millions‐of‐consumers‐atrisk/ 2019.

3. StaDART: Addressing the problem of dynamic code updates in the security analysis of android applications;Ahmad M.;Journal of Systems and Software,2020

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1. A Novel Permission Filtering Approach for Android Malware Detection and Malware Family Classification;2023 19th International Conference on Mobility, Sensing and Networking (MSN);2023-12-14

2. Comparative Study of Static Analysis and Machine Learning Approaches for Detecting Android Banking Malware;2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA);2023-10-10

3. Success and failure rate prediction of Android Application using Machine Learning;2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON);2023-02-08

4. Android malware detection method based on highly distinguishable static features and DenseNet;PLOS ONE;2022-11-23

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