Deep Stacking Network for Intrusion Detection

SAAE-DNN: Deep Learning Method on Intrusion Detection

(2020) Chaofei Tang et al.   Symmetry-Basel

Stacked Autoencoder-Based Intrusion Detection System to Combat Financial Fraudulent

(2020) Ghulam Muhammad et al.   IEEE Internet of Things Journal

Building an Effective Intrusion Detection System Using the Modified Density Peak Clustering Algorithm and Deep Belief Networks

(2019) Yanqing Yang et al.   Applied Sciences-Basel

Improving the Classification Effectiveness of Intrusion Detection by Using Improved Conditional Variational AutoEncoder and Deep Neural Network

(2019) Yanqing Yang et al.   SENSORS

Evolving deep learning architectures for network intrusion detection using a double PSO metaheuristic

(2019) Wisam Elmasry et al.   Computer Networks

A New Intrusion Detection System Based on Fast Learning Network and Particle Swarm Optimization

(2018) Mohammed Hasan Ali et al.   IEEE Access

A Novel Intrusion Detection Model for a Massive Network Using Convolutional Neural Networks

(2018) Kehe Wu et al.   IEEE Access

A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks

(2017) Chuanlong Yin et al.   IEEE Access

An effective intrusion detection framework based on MCLP/SVM optimized by time-varying chaos particle swarm optimization

(2016) Seyed Mojtaba Hosseini Bamakan et al.   NEUROCOMPUTING

Feature selection algorithm based on bare bones particle swarm optimization

(2015) Yong Zhang et al.   NEUROCOMPUTING

Histogram-based traffic anomaly detection

(2010) Andreas Kind et al.   IEEE Transactions on Network and Service Management