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 …
operation in hostile environments and limited resources, which pose challenges for hosting …
Internet of things intrusion detection: Centralized, on-device, or federated learning?
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 …
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
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 …
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
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 …
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 …
based systems are insufficient, driving the integration of machine learning (ML) for effective …
FeCo: Boosting intrusion detection capability in IoT networks via contrastive learning
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 …
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
This paper presents a heterogeneous federated ensemble model for intrusion detection
system, employing a semisupervised novelty detection technique-the baseline K-means …
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 …
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 …
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 …
and smart services has rapidly expanded the threat landscape for IoT devices. Researchers …