Unsupervised deep learning approach for network intrusion detection combining convolutional autoencoder and one-class SVM

One-dimensional convolutional auto-encoder-based feature learning for fault diagnosis of multivariate processes

(2020) Shumei Chen et al.   JOURNAL OF PROCESS CONTROL

An Enhanced Design of Sparse Autoencoder for Latent Features Extraction Based on Trigonometric Simplexes for Network Intrusion Detection Systems

(2020) Hassan Musafer et al.   Electronics

Cascade of One Class Classifiers for Water Level Anomaly Detection

(2020) Fabian Hann Shen Tan et al.   Electronics

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

Using CNN for facial expression recognition: a study of the effects of kernel size and number of filters on accuracy

(2019) Abhinav Agrawal et al.   VISUAL COMPUTER

An intelligent intrusion detection system

(2019) Nevrus Kaja et al.   APPLIED INTELLIGENCE

RAMD: registry-based anomaly malware detection using one-class ensemble classifiers

(2019) Asghar Tajoddin et al.   APPLIED INTELLIGENCE

Feature selection for intrusion detection using new multi-objective estimation of distribution algorithms

(2019) Sofiane Maza et al.   APPLIED INTELLIGENCE

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

(2019) Yanqing Yang et al.   SENSORS

Designing online network intrusion detection using deep auto-encoder Q-learning

(2019) Chayoung Kim et al.   COMPUTERS & ELECTRICAL ENGINEERING

Deep learning approaches for anomaly-based intrusion detection systems: A survey, taxonomy, and open issues

(2019) Arwa Aldweesh et al.   KNOWLEDGE-BASED SYSTEMS

Review of intrusion detection systems based on deep learning techniques: coherent taxonomy, challenges, motivations, recommendations, substantial analysis and future directions

(2019) A. M. Aleesa et al.   NEURAL COMPUTING & APPLICATIONS

A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach

(2019) Cosimo Ieracitano et al.   NEUROCOMPUTING

Hyperparameter selection of one-class support vector machine by self-adaptive data shifting

(2018) Siqi Wang et al.   PATTERN RECOGNITION

Effective Feature Extraction via Stacked Sparse Autoencoder to Improve Intrusion Detection System

(2018) Binghao Yan et al.   IEEE Access

Deep Learning Approach Combining Sparse Autoen-coder with SVM for Network Intrusion Detection

(2018) Majjed Al-Qatf et al.   IEEE Access

Ramp Loss based robust one-class SVM

(2017) Yingchao Xiao et al.   PATTERN RECOGNITION LETTERS

Network Intrusion Detection through Stacking Dilated Convolutional Autoencoders

(2017) Yang Yu et al.   Security and Communication Networks

Auto-encoder based dimensionality reduction

(2016) Yasi Wang et al.   NEUROCOMPUTING

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security

(2016) Min-Joo Kang et al.   PLoS One

One-class classification: taxonomy of study and review of techniques

(2014) Shehroz S. Khan et al.   KNOWLEDGE ENGINEERING REVIEW

An experimental study on stability and generalization of extreme learning machines

(2014) Aimin Fu et al.   International Journal of Machine Learning and Cybernetics