Machine learning for anomaly detection: A systematic review

AB Nassif, MA Talib, Q Nasir, FM Dakalbab - Ieee Access, 2021 - ieeexplore.ieee.org
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges

A Khraisat, A Alazab - Cybersecurity, 2021 - Springer
Abstract The Internet of Things (IoT) has been rapidly evolving towards making a greater
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …

Comparative analysis of intrusion detection systems and machine learning-based model analysis through decision tree

Z Azam, MM Islam, MN Huda - IEEE Access, 2023 - ieeexplore.ieee.org
Cyber-attacks pose increasing challenges in precisely detecting intrusions, risking data
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …

Machine learning technology in biodiesel research: A review

M Aghbashlo, W Peng, M Tabatabaei… - Progress in Energy and …, 2021 - Elsevier
Biodiesel has the potential to significantly contribute to making transportation fuels more
sustainable. Due to the complexity and nonlinearity of processes for biodiesel production …

An improved anomaly detection model for IoT security using decision tree and gradient boosting

M Douiba, S Benkirane, A Guezzaz… - The Journal of …, 2023 - Springer
Abstract Internet of Things (IoT) represents a massive deployment of connected, intelligent
devices that communicate directly in private, public, and professional environments without …

RTIDS: A robust transformer-based approach for intrusion detection system

Z Wu, H Zhang, P Wang, Z Sun - IEEE Access, 2022 - ieeexplore.ieee.org
Due to the rapid growth in network traffic and increasing security threats, Intrusion Detection
Systems (IDS) have become increasingly critical in the field of cyber security for providing …

Survey of intrusion detection systems: techniques, datasets and challenges

A Khraisat, I Gondal, P Vamplew, J Kamruzzaman - Cybersecurity, 2019 - Springer
Cyber-attacks are becoming more sophisticated and thereby presenting increasing
challenges in accurately detecting intrusions. Failure to prevent the intrusions could degrade …

lIDS-SIoEL: intrusion detection framework for IoT-based smart environments security using ensemble learning

C Hazman, A Guezzaz, S Benkirane, M Azrour - Cluster Computing, 2023 - Springer
Smart cities are being enabled all around the world by Internet of Things (IoT) applications.
A smart city idea necessitates the integration of information and communication …

Anomaly-based intrusion detection from network flow features using variational autoencoder

S Zavrak, M Iskefiyeli - IEEe Access, 2020 - ieeexplore.ieee.org
The rapid increase in network traffic has recently led to the importance of flow-based
intrusion detection systems processing a small amount of traffic data. Furthermore, anomaly …

Survey on SDN based network intrusion detection system using machine learning approaches

N Sultana, N Chilamkurti, W Peng… - Peer-to-Peer Networking …, 2019 - Springer
Abstract Software Defined Networking Technology (SDN) provides a prospect to effectively
detect and monitor network security problems ascribing to the emergence of the …