Localization and Detection of Multiple Attacks in Wireless Sensor Networks Using Artificial Neural Network

Table 10

Comparative analysis of the proposed technique with recent attack detection models using UNSW-NB 15 dataset.

Author	Method	Accuracy	Precision	Recall	F1-score
Pasikhani,et al. [72]	RL-IDS	98.35	98.36	97.04	98.34
Upadhyay et al. [73]	GBFS-IDS	92.96	92.50	92.40	92.44
Abdan and H. Seno [11]	ML-ID	98.9	87.7	99.6	92.78
Gudla et al. [74]	DI-ADS	99.44	99.02	99.60	99.30
Alghamdi [75]	PO-CFNN	99.86	99.89	99.58	99.72
Khilar et al. [76]	DNN-CSO	99.46	99.75	99.62	99.76
Proposed system	MLPANN	100.00	100.00	100.00	100.00