Statistics

Operating system

Algorithm

Data mining

Mean squared error

Artificial intelligence

Network packet

Multilayer perceptron

CloudSim

Computer network

Mathematics

Intrusion detection system

Computer science

Artificial neural network

Cluster analysis

Cloud computing

Statistic

Artificial bee colony algorithm

ICT Express

This paper proposes a new intrusion detection system (IDS) based on a combination of a multilayer perceptron (MLP) network, and artificial bee colony (ABC) and fuzzy clustering algorithms. Normal and abnormal network traffic packets are identified by the MLP, while the MLP training is done by the ABC algorithm through optimizing the values of linkage weights and biases. The CloudSim simulator and NSL-KDD dataset are used to verify the proposed method. Mean absolute error (MAE), root mean square error (RMSE), and the kappa statistic are considered as evaluation criteria. The obtained results have indicated the superiority of the proposed method in comparison with state-of-the-art methods.

Intrusion detection for cloud computing using neural networks and artificial bee colony optimization algorithm