A Systematic Overview of Android Malware Detection-Reference-Cited by-同舟云学术

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A Systematic Overview of Android Malware Detection

Published:2021-12-14 Issue: Volume: Page:1-33
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Meijin Li¹^ORCID,Zhiyang Fang²^ORCID,Junfeng Wang³,Luyu Cheng⁴,Qi Zeng³^ORCID,Tao Yang³^ORCID,Yinwei Wu¹,Jiaxuan Geng³

Affiliation:

1. College of Software Engineering, Sichuan University, Chengdu, China

2. School of Cyber Science and Engineering, Sichuan University, Chengdu, China

3. College of Computer Science, Sichuan University, Chengdu, China

4. School of Business, Sichuan University, Chengdu, China

Funder

National Natural Science Foundation of China

Basic Research Program of China

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2021.2007327

Reference144 articles.

1. Identifying Android malware using dynamically obtained features

2. Mining nested flow of dominant APIs for detecting android malware

3. Intelligent mobile malware detection using permission requests and API calls

5. A Survey on Android Malware Detection Techniques Using Machine Learning Algorithms.

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Android Malware Detection using HexCode Features;2024-06-26

2. An efficient security testing for android application based on behavior and activities using RFE-MLP and ensemble classifier;Multimedia Tools and Applications;2024-06-20

3. DETECTION OF ANDROID MALWARE USING DEEP LEARNING ENSEMBLE WITH CHEETAH-OPTIMIZED FEATURE SELECTION;Advances and Applications in Discrete Mathematics;2024-06-06

4. A systematic literature review on Windows malware detection: Techniques, research issues, and future directions;Journal of Systems and Software;2024-03

5. Machine Learning for Android Malware Detection: Mission Accomplished? A Comprehensive Review of Open Challenges and Future Perspectives;Computers & Security;2024-03

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