… in network security is intrusion detection systems (IDSs) which try to keep security at the
highest level. This paper addresses a IDS using a 2-layered feed-forward neural network. In …

… In this paper, we propose a methodology based on feed-forward neural network for
intrusion detection. Better performances than traditional machine learning techniques can be …

… This paper compares Pattern Recognition and Feed-Forward Neural network on intrusion
detection and explores that which model delivers excellent results in term of Accuracy, MCC, R…

… In this paper, a Deep Learning model using a feed-forward neural network is introduced
for intrusion detection. Experiment results demonstrated that the accuracy of 99% is acchieved …

… In this paper, a deep learning binomial classifier for Network Intrusion Detection System
is proposed and experimentally evaluated using the UNSW-NB15 dataset. Three different …

… scale, intrusion detection is … intrusion detection system for the security in each occasion for
the sensitive users, governments, enterprises and governments. Network Intrusion Detection (…

… feed-forward artificial neural network model that enables precise estimates of the k-barrier
count for effective intrusion detection … to learn and assess the feed-forward ANN model. The …

… the development of a residual feedforward neural network-based intrusion detection system.
The RFNN algorithm was proposed to reduce overfitting, improve detection accuracy, and …

… intrusion detection system: Gao et al. [9] have presented a novel for network intrusion detection
… [18] have introduced intrusion detection system by using intelligent data mining in weka …

… intrusion detection system is introduced to detect routing attacks in wireless sensor networks
using fuzzy and feed-forward … an average detection rate of 97.8% and a maximum detection …