TFDroid: Android Malware Detection by Topics and Sensitive Data Flows Using Machine Learning Techniques-Reference-Cited by-同舟云学术

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TFDroid: Android Malware Detection by Topics and Sensitive Data Flows Using Machine Learning Techniques

Published:2019-03 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)
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Author:

Lou Songhao,Cheng Shaoyin,Huang Jingjing,Jiang Fan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8703750/8710850/08711179.pdf?arnumber=8711179

Cited by 34 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. Comparative Analysis of Machine Learning Models for Android Malware Detection;Sakarya University Journal of Science;2024-06-30

2. Research on Personal Privacy Security Detection Techniques for Android Applications;2024 9th International Conference on Electronic Technology and Information Science (ICETIS);2024-05-17

3. A New Android Malware Detection Approach Using Multilayer Stacking;2024 10th International Conference on Web Research (ICWR);2024-04-24

4. SecuDroid : Android Malware Detection using ML classifier on Static Features;2024 2nd International Conference on Networking and Communications (ICNWC);2024-04-02

5. An effective deep learning scheme for android malware detection leveraging performance metrics and computational resources;Intelligent Decision Technologies;2024-02-20

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