Collaborative Anomaly-based Intrusion Detection Systems in Lightweight IoT

S Hajj - 2023 - theses.hal.science
Lightweight Internet-of-Things (IoT) devices are susceptible to network attacks due to their
operation in hostile environments and limited resources, which pose challenges for hosting …

Internet of things intrusion detection: Centralized, on-device, or federated learning?

SA Rahman, H Tout, C Talhi, A Mourad - IEEE Network, 2020 - ieeexplore.ieee.org
With the ever increasing number of cyber-attacks, internet of Things (ioT) devices are being
exposed to serious malware, attacks, and malicious activities alongside their development …

[HTML][HTML] Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks

X Sáez-de-Cámara, JL Flores, C Arellano, A Urbieta… - Computers & …, 2023 - Elsevier
There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover,
the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse …

AOC-IDS: Autonomous Online Framework with Contrastive Learning for Intrusion Detection

X Zhang, R Zhao, Z Jiang, Z Sun, Y Ding… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid expansion of the Internet of Things (IoT) has raised increasing concern about
targeted cyber attacks. Previous research primarily focused on static Intrusion Detection …

Unveiling the IoT's dark corners: anomaly detection enhanced by ensemble modelling

J Jose, JE Judith - Automatika, 2024 - Taylor & Francis
The growing Internet of Things (IoT) landscape requires robust security; traditional rule-
based systems are insufficient, driving the integration of machine learning (ML) for effective …

FeCo: Boosting intrusion detection capability in IoT networks via contrastive learning

N Wang, Y Chen, Y Hu, W Lou… - IEEE INFOCOM 2022 …, 2022 - ieeexplore.ieee.org
Over the last decade, Internet of Things (IoT) has permeated our daily life with a broad range
of applications. However, a lack of sufficient security features in IoT devices renders IoT …

Cross-layer Federated Heterogeneous Ensemble Learning for Lightweight IoT Intrusion Detection System

S Hajj, J Azar, JB Abdo, J Demerjian… - 2023 IEEE 10th …, 2023 - ieeexplore.ieee.org
This paper presents a heterogeneous federated ensemble model for intrusion detection
system, employing a semisupervised novelty detection technique-the baseline K-means …

[PDF][PDF] Exploring Unsupervised One-Class Classifiers for Lightweight Intrusion Detection in IoT Systems

S Golestani, D Makaroff - researchgate.net
The Internet of Things (IoT) has revolutionized numerous domains, but security and privacy
remain significant concerns. Massive amounts of IoT data poses challenges for a centralized …

[PDF][PDF] Strengthening IoT Security: Leveraging Machine Learning for Improved Detection of Intrusions in Connected Networks

B Hurry - 2024 - easychair.org
The rapid proliferation of Internet of Things (IoT) devices has led to unprecedented
connectivity, revolutionizing various aspects of our lives. However, this interconnectedness …

PRIVACY-PRESERVING DECENTRALIZED INTRUSION DETECTION SYSTEM FOR IOT DEVICES USING DEEP LEARNING

A TABASSUM - 2022 - qspace.qu.edu.qa
The convergence of advanced networking, breakthrough distributed systems technologies,
and smart services has rapidly expanded the threat landscape for IoT devices. Researchers …