DynamicFusion
所属分类：聚类算法
开发工具：Jupyter Notebook
文件大小：500KB
下载次数：0
上传日期：2022-04-15 16:50:17
上 传 者：
sh-1993
说明： 基于Logistic回归和动态特征选择的android恶意软件检测方法
(Logistic regression and dynamic feature selection based android malware detection approach)
文件列表:
Feature Selection (Test) -Drebin.ipynb (41666, 2022-04-16)
Feature Selection (Test) -malgenome.ipynb (53887, 2022-04-16)
data (0, 2022-04-16)
data\drebin-215-dataset-5560malware-9476-benign.csv (6495552, 2022-04-16)
data\malgenome215dataset1260malware2539benign.csv (1649383, 2022-04-16)
# DynamicFusion- Logistic Regression based Android Malware Detection Approach
## Machine configuration
- `OS:` Windows 10 *** bit
- `RAM:` 8 GB
- `Processor:` 11th Gen Intel(R) Core(TM) i5
## Software requirements
- Anaconda3 2021.11 (Python 3.9.7 ***-bit)
## Classifier
- Logistic Regression
## Dataset
- The experiment is done using `Malgenome-215` and `Drebin-215` datasets.
## Publication followed
- S. Y. Yerima and S. Sezer, "DroidFusion: A Novel Multilevel Classifier Fusion Approach for Android Malware Detection," in IEEE Transactions on Cybernetics, vol. 49, no. 2, pp. 453-466, Feb. 2019, doi: 10.1109/TCYB.2017.2777960.
- Xu, R., Li, M., Yang, Z. et al. Dynamic feature selection algorithm based on Q-learning mechanism. Appl Intell 51, 7233“7244 (2021). https://doi.org/10.1007/s10489-021-02257-x
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