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FAMD: A Fast Multifeature Android Malware Detection Framework, Design, and Implementation

  • Published:2020 Issue: Volume:8 Page:194729-194740
  • ISSN:2169-3536
  • Container-title:IEEE Access
  • language:
  • Short-container-title:IEEE Access

Author:

Bai HongpengORCID,Xie NannanORCID,Di XiaoqiangORCID,Ye Qing

Funder

13th Five-Year Science and Technology Research Project of the Education Department of Jilin Province

Innovation Fund of Changchun University of Science and Technology

Fund of the Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 53 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. Detection and analysis of android malwares using hybrid dual Path bi-LSTM Kepler dynamic graph convolutional network;International Journal of Machine Learning and Cybernetics;2024-08-19

2. GMADV: An android malware variant generation and classification adversarial training framework;Journal of Information Security and Applications;2024-08

3. Malware Detection and Classification for URLs using Ensemble Learning;2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN);2024-05-03

4. Effective and Efficient Android Malware Detection and Category Classification Using the Enhanced KronoDroid Dataset;Security and Communication Networks;2024-04-08

5. Improving the forecast performance of landslide susceptibility mapping by using ensemble gradient boosting algorithms;Environment, Development and Sustainability;2024-03-14
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