ADSAD: An unsupervised attention-based discrete sequence anomaly detection framework for network security analysis

BLATTA: Early Exploit Detection on Network Traffic with Recurrent Neural Networks

(2020) Baskoro A. Pratomo et al.   Security and Communication Networks

Multiclass Classification Procedure for Detecting Attacks on MQTT-IoT Protocol

(2019) Hector Alaiz-Moreton et al.   COMPLEXITY

Deep-anomaly: Fully convolutional neural network for fast anomaly detection in crowded scenes

(2018) Mohammad Sabokrou et al.   COMPUTER VISION AND IMAGE UNDERSTANDING

Early-stage malware prediction using recurrent neural networks

(2018) Matilda Rhode et al.   COMPUTERS & SECURITY

Web traffic anomaly detection using C-LSTM neural networks

(2018) Tae-Young Kim et al.   EXPERT SYSTEMS WITH APPLICATIONS

HAST-IDS: Learning Hierarchical Spatial-Temporal Features Using Deep Neural Networks to Improve Intrusion Detection

(2018) Wei Wang et al.   IEEE Access

An anomaly detection system based on variable N-gram features and one-class SVM

(2017) Wael Khreich et al.   INFORMATION AND SOFTWARE TECHNOLOGY

OCPAD: One class Naive Bayes classifier for payload based anomaly detection

(2016) Mayank Swarnkar et al.   EXPERT SYSTEMS WITH APPLICATIONS

Detecting zero-day attacks using context-aware anomaly detection at the application-layer

(2016) Patrick Duessel et al.   International Journal of Information Security

A Semantic Approach to Host-Based Intrusion Detection Systems Using Contiguousand Discontiguous System Call Patterns

(2013) Gideon Creech et al.   IEEE TRANSACTIONS ON COMPUTERS

HMMPayl: An intrusion detection system based on Hidden Markov Models

(2011) Davide Ariu et al.   COMPUTERS & SECURITY

McPAD: A multiple classifier system for accurate payload-based anomaly detection

(2008) Roberto Perdisci et al.   Computer Networks