A comparative analysis of machine learning techniques for IoT intrusion detection

J Vitorino, R Andrade, I Praça, O Sousa… - … on Foundations and …, 2021 - Springer
The digital transformation faces tremendous security challenges. In particular, the growing
number of cyber-attacks targeting Internet of Things (IoT) systems restates the need for a …

IDS-EFS: Ensemble feature selection-based method for intrusion detection system

Y Akhiat, K Touchanti, A Zinedine… - Multimedia Tools and …, 2024 - Springer
Network intrusions have predominantly increased following the rapid expansion of networks
in different areas such as social networking, e-learning, e-business, etc. With the rapid …

An intelligent intrusion detection system using hybrid deep learning approaches in cloud environment

A Sharon, P Mohanraj, TE Abraham, B Sundan… - … , and Signal Processing, 2022 - Springer
Abstract An Intrusion Detection System (IDS) detects suspicious activities and sends alerts
when they are found. Based on these alerts, the issue is investigated, and appropriate …

A Review of Intrusion Detection Systems Using Machine Learning: Attacks, Algorithms and Challenges

JL Gutierrez-Garcia, E Sanchez-DelaCruz… - Future of Information …, 2023 - Springer
Cybersecurity has become a priority concern of the digital society. Many attacks are
becoming more sophisticated, requiring strengthening the strategies of identification …

Intrusion detection in cluster‐based wireless sensor networks: Current issues, opportunities and future research directions

A John, IFB Isnin… - IET Wireless Sensor …, 2024 - Wiley Online Library
Wireless sensor network (WSN) cluster‐based architecture is a system designed to control
and monitor specific events or phenomena remotely, and one of the important concerns that …

Meta pseudo labels for anomaly detection via partially observed anomalies

S Zhao, Z Yu, S Li, X Wang, TG Marbach… - … Applications of Artificial …, 2023 - Elsevier
General anomaly detection has been an important research due to its broad and significant
applications. Those algorithms that are based on weakly supervised or partially observed …

Time-Series Modeling for Intrusion Detection Systems

K Psychogyios, S Bourou, A Papadakis… - … Computing and Artificial …, 2023 - Springer
The advent of computer networks and the Internet has drastically altered the means by
which we share information & interact with each other. However, this technological …

[HTML][HTML] Intrusion detection system: a comparative study of machine learning-based IDS

A Singh, J Prakash, G Kumar - 2022 - europepmc.org
Due to the Covid-19 pandemic, there has been a significant rise in the amount of data
processed and transferred to any communication network. The use of encrypted data, the …

Simpler is better: On the use of autoencoders for intrusion detection

M Catillo, A Pecchia, U Villano - International Conference on the Quality of …, 2022 - Springer
The ever-growing occurrence of computer security incidents calls for advanced intrusion
detection techniques. A wide body of literature dealing with Intrusion Detection Systems …

An intrusion detection system for blackhole attack detection and isolation in RPL based IoT using ANN

C Prajisha, AR Vasudevan - International Advanced Computing …, 2021 - Springer
Abstract Routing Protocol for Low Power and Lossy Networks (RPL) is a simple and
lightweight routing protocol for Internet of Things (IoT). RPL-based IoT networks are prone to …