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Table 4 Prediction accuracy of the selected model with respect to each dataset

From: A deep learning framework for predicting cyber attacks rates

Dataset

MSE

MAD

PMAD

MAPE

ARIMA

I

40,054,811

5,038.95

0.1352803

0.1378065

II

100,487,103

6,763.351

0.2618205

0.314159

III

47,486,461

3,478.307

0.2212886

0.2573687

IV

17,002,355

2,353.409

0.8187241

0.8372556

V

456,948,359

15,919.9

0.4062245

0.5932768

ARMA+GARCH

I

38,077,842

4908.317

0.1317732

0.1361043

II

93,164,156

5,861.041

0.2268906

0.2530479

III

56,736,538

3431.358

0.2183016

0.2395564

IV

3,837,969

1,356.005

0.4717387

0.5876807

V

553,535,870

16,671.04

0.4253909

0.5267857

Hybrid

I

36,177,293.39

4,652.507998

0.124905523

0.127347065

II

93017462.9

6169.871649

0.238845915

0.281375049

III

39,425,972.04

2,807.162152

0.178590549

0.206457204

IV

3,162,758.321

1,063.447725

0.369961347

0.384547602

V

493,400,639.5

16,787.20604

0.385329179

0.516025677