Network Intrusion Detection Based on Novel Feature Selection Model and Various Recurrent Neural Networks

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

Deep Learning Method for Denial of Service Attack Detection Based on Restricted Boltzmann Machine

(2018) Yadigar Imamverdiyev et al.   Big Data

A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks

(2017) Chuanlong Yin et al.   IEEE Access

A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks

(2016) Tao Ma et al.   SENSORS

Detection of Denial-of-Service Attacks Based on Computer Vision Techniques

(2015) Zhiyuan Tan et al.   IEEE TRANSACTIONS ON COMPUTERS

Network anomaly detection with the restricted Boltzmann machine

(2013) Ugo Fiore et al.   NEUROCOMPUTING

Design of an Evolutionary Approach for Intrusion Detection

(2013) Gulshan Kumar et al.   TheScientificWorldJOURNAL

Toward developing a systematic approach to generate benchmark datasets for intrusion detection

(2012) Ali Shiravi et al.   COMPUTERS & SECURITY

Intrusion detection system: A comprehensive review

(2012) Hung-Jen Liao et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

A survey of intrusion detection techniques in Cloud

(2012) Chirag Modi et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

Swarm intelligence in intrusion detection: A survey

(2011) C. Kolias et al.   COMPUTERS & SECURITY

Anomaly detection in wireless sensor networks: A survey

(2011) Miao Xie et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

A triangle area based nearest neighbors approach to intrusion detection

(2009) Chih-Fong Tsai et al.   PATTERN RECOGNITION

Anomaly-based network intrusion detection: Techniques, systems and challenges

(2008) P. García-Teodoro et al.   COMPUTERS & SECURITY