N-Gram, Semantic-Based Neural Network for Mobile Malware Network Traffic Detection

Table 4

Description of detecting performance metrics of different domain composition architectures with different text sizes.

Domain composition type number	Evaluation metrics	Text size (byte) of the transformed data from network flow
		200	500	700	1000	1200	1500
1	Precision	0.775	0.828	0.935	0.942	0.945	0.950
	Recall	0.657	0.724	0.820	0.863	0.863	0.864
	F1-score	0.711	0.773	0.873	0.900	0.902	0.905
	Accuracy	0.706	0.773	0.874	0.903	0.905	0.907
2	Precision	0.773	0.821	0.924	0.929	0.930	0.933
	Recall	0.657	0.721	0.810	0.850	0.849	0.854
	F1-score	0.710	0.768	0.863	0.888	0.888	0.891
	Accuracy	0.707	0.769	0.863	0.890	0.891	0.894
3	Precision	0.778	0.818	0.918	0.920	0.924	0.926
	Recall	0.659	0.720	0.805	0.843	0.844	0.847
	F1-score	0.714	0.765	0.858	0.880	0.883	0.885
	Accuracy	0.709	0.766	0.858	0.883	0.886	0.887
4	Precision	0.777	0.822	0.912	0.906	0.912	0.912
	Recall	0.661	0.720	0.798	0.831	0.832	0.836
	F1-score	0.714	0.714	0.851	0.867	0.870	0.872
	Accuracy	0.712	0.762	0.851	0.870	0.873	0.875
5	Precision	0.770	0.809	0.902	0.894	0.859	0.896
	Recall	0.660	0.712	0.791	0.820	0.821	0.823
	F1-score	0.711	0.757	0.843	0.855	0.856	0.858
	Accuracy	0.708	0.758	0.843	0.859	0.860	0.862
6	Precision	0.784	0.836	0.900	0.946	0.944	0.949
	Recall	0.662	0.732	0.799	0.862	0.864	0.863
	F1-score	0.718	0.781	0.847	0.902	0.902	0.904
	Accuracy	0.713	0.781	0.848	0.904	0.905	0.906
7	Precision	0.775	0.822	0.926	0.931	0.934	0.936
	Recall	0.659	0.720	0.815	0.861	0.862	0.863
	F1-score	0.712	0.768	0.867	0.895	0.896	0.898
	Accuracy	0.709	0.774	0.868	0.898	0.900	0.901
8	Precision	0.847	0.894	0.954	0.969	0.971	0.971
	Recall	0.715	0.784	0.848	0.880	0.881	0.881
	F1-score	0.775	0.836	0.898	0.922	0.924	0.924
	Accuracy	0.772	0.836	0.899	0.924	0.925	0.926
9	Precision	0.848	0.896	0.954	0.969	0.971	0.971
	Recall	0.716	0.784	0.849	0.880	0.881	0.882
	F1-score	0.776	0.836	0.899	0.923	0.924	0.924
	Accuracy	0.772	0.837	0.899	0.924	0.925	0.926