A deep density based and self-determining clustering approach to label unknown traffic

Building Auto-Encoder Intrusion Detection System based on random forest feature selection

(2020) XuKui Li et al.   COMPUTERS & SECURITY

I-SiamIDS: an improved Siam-IDS for handling class imbalance in network-based intrusion detection systems

(2020) Punam Bedi et al.   APPLIED INTELLIGENCE

Clustering of unknown protocol messages based on format comparison

(2020) Fanghui Sun et al.   Computer Networks

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

(2019) Yanqing Yang et al.   SENSORS

A survey of network-based intrusion detection data sets

(2019) Markus Ring et al.   COMPUTERS & SECURITY

adVAE: A self-adversarial variational autoencoder with Gaussian anomaly prior knowledge for anomaly detection

(2019) Xuhong Wang et al.   KNOWLEDGE-BASED SYSTEMS

Learning Sparse Representation With Variational Auto-Encoder for Anomaly Detection

(2018) Jiayu Sun et al.   IEEE Access

How to trick the Borg: threat models against manual and automated techniques for detecting network attacks

(2018) Carl Sabottke et al.   COMPUTERS & SECURITY

Hierarchical Spectral Consensus Clustering for Group Analysis of Functional Brain Networks

(2015) Alp Ozdemir et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

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

(2012) Ali Shiravi et al.   COMPUTERS & SECURITY

A novel method of mining network flow to detect P2P botnets

(2012) Shu-Chiung Lin et al.   Peer-to-Peer Networking and Applications