Bayesian Hyperparameter Optimization for Deep Neural Network-Based Network Intrusion Detection. (arXiv:2207.09902v1 [cs.CR])

Traditional network intrusion detection approaches encounter feasibility and
sustainability issues to combat modern, sophisticated, and unpredictable
security attacks. Deep neural networks (DNN) have been successfully applied for
intrusion detection problems. The optimal use of DNN-based classifiers requires
careful tuning of the hyper-parameters. Manually tuning the hyperparameters is
tedious, time-consuming, and computationally expensive. Hence, there is a need
for an automatic technique to find optimal hyperparameters for the best use of
DNN in intrusion detection. This paper proposes a novel Bayesian …

detection intrusion intrusion detection network neural network optimization