Deep learning-based intrusion detection systems: a systematic review
Nowadays, the ever-increasing complication and severity of security attacks on computer
networks have inspired security researchers to incorporate different machine learning …
networks have inspired security researchers to incorporate different machine learning …
CICIDS2017 dataset: performance improvements and validation as a robust intrusion detection system testbed
A Boukhamla, JC Gaviro - International Journal of …, 2021 - inderscienceonline.com
Nowadays, network security represents a huge challenge on the fight against new
sophisticated attacks. Many intrusion detection systems (IDS) have been developed and …
sophisticated attacks. Many intrusion detection systems (IDS) have been developed and …
Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation
Intrusion detection systems (IDSs) are intrinsically linked to a comprehensive solution of
cyberattacks prevention instruments. To achieve a higher detection rate, the ability to design …
cyberattacks prevention instruments. To achieve a higher detection rate, the ability to design …
Classification hardness for supervised learners on 20 years of intrusion detection data
This article consolidates analysis of established (NSL-KDD) and new intrusion detection
datasets (ISCXIDS2012, CICIDS2017, CICIDS2018) through the use of supervised machine …
datasets (ISCXIDS2012, CICIDS2017, CICIDS2018) through the use of supervised machine …
An evaluation of machine learning-based anomaly detection in a SCADA system using the modbus protocol
B Phillips, E Gamess, S Krishnaprasad - Proceedings of the 2020 ACM …, 2020 - dl.acm.org
Supervisory Control and Data Acquisition (SCADA) systems have been designed with the
assumption that the system would run within a closed environment. They have only …
assumption that the system would run within a closed environment. They have only …
Improving SIEM for critical SCADA water infrastructures using machine learning
Abstract Network Control Systems (NAC) have been used in many industrial processes.
They aim to reduce the human factor burden and efficiently handle the complex process and …
They aim to reduce the human factor burden and efficiently handle the complex process and …
Ocsvm model combined with k-means recursive clustering for intrusion detection in scada systems
LA Maglaras, J Jiang - 10th International conference on …, 2014 - ieeexplore.ieee.org
Intrusion detection in Supervisory Control and Data Acquisition (SCADA) systems is of major
importance nowadays. Most of the systems are designed without cyber security in mind …
importance nowadays. Most of the systems are designed without cyber security in mind …
Multi-stage learning framework using convolutional neural network and decision tree-based classification for detection of DDoS pandemic attacks in SDN-based …
Supervisory Control and Data Acquisition (SCADA) systems, which play a critical role in
monitoring, managing, and controlling industrial processes, face flexibility, scalability, and …
monitoring, managing, and controlling industrial processes, face flexibility, scalability, and …
SCADA systems: vulnerabilities and remediation
JD Fernandez, AE Fernandez - Journal of Computing Sciences in …, 2005 - dl.acm.org
Supervisory Control and Data Acquisition, otherwise known as SCADA, is a system for
gathering real time data, controlling processes, and monitoring equipment from remote …
gathering real time data, controlling processes, and monitoring equipment from remote …
Ensemble learning for threat classification in network intrusion detection on a security monitoring system for renewable energy
HC Lin, P Wang, KM Chao, WH Lin, ZY Yang - Applied Sciences, 2021 - mdpi.com
Most approaches for detecting network attacks involve threat analyses to match the attack to
potential malicious profiles using behavioral analysis techniques in conjunction with packet …
potential malicious profiles using behavioral analysis techniques in conjunction with packet …