Novel class probability features for optimizing network attack detection with machine learning

A Raza, K Munir, MS Almutairi, R Sehar - IEEE Access, 2023 - ieeexplore.ieee.org
Network attacks refer to malicious activities exploiting computer network vulnerabilities to
compromise security, disrupt operations, or gain unauthorized access to sensitive …

IDRandom-Forest: Advanced Random Forest for Real-time Intrusion Detection

M Azhar, S Perveen, A Iqbal, B Lee - IEEE Access, 2024 - ieeexplore.ieee.org
In the last decade, with the increase in cyberattacks the privacy of network traffic has
become a critical issue. Currently, simple network intrusion detection techniques are …

Enhanced Grey Wolf Optimization (EGWO) and random forest based mechanism for intrusion detection in IoT networks

SS Alqahtany, A Shaikh, A Alqazzaz - Scientific Reports, 2025 - nature.com
Smart devices are enabled via the Internet of Things (IoT) and are connected in an
uninterrupted world. These connected devices pose a challenge to cybersecurity systems …

Anomaly detection in network traffic with ELSC learning algorithm

MM Khan, MZ Rehman, A Khan… - Electronics Letters, 2024 - Wiley Online Library
In recent years, the internet has not only enhanced the quality of our lives but also made us
susceptible to high‐frequency cyber‐attacks on communication networks. Detecting such …

A Comparative Analysis on Ensemble Learning and Deep Learning Based Intrusion Detection Systems over the NCC2 Dataset

S Belkacem - International Conference on Information Technology …, 2024 - Springer
Intrusion detection systems (IDS) are effective countermeasures to ensure Internet of Things
(IoT) network security. IDS are employed to guarantee data privacy and assess network …

IoT-Based Line Breakage Detection & Alerting System for Overhead Distribution Lines

BN Abhin, KP Abhinav, AK RJ… - … on Smart Power …, 2024 - ieeexplore.ieee.org
Safety is a paramount concern in power system design and operation. Line breakages in
distribution systems can be elusive due to their diverse characteristics and intermittent …

A Systematic Analysis and Review on Intrusion Detection Systems Using Machine Learning and Deep Learning Algorithms

SL Jacob, PS Habibullah - Journal of Computational and …, 2022 - ojs.bonviewpress.com
An intrusion detection system (IDS) is crucial for defending computer networks and systems
from cyberattacks, unauthorized entry, and harmful activities. Machine learning (ML) and …