[HTML][HTML] Network anomaly detection methods in IoT environments via deep learning: A Fair comparison of performance and robustness

G Bovenzi, G Aceto, D Ciuonzo, A Montieri… - Computers & …, 2023 - Elsevier
Abstract The Internet of Things (IoT) is a key enabler in closing the loop in Cyber-Physical
Systems, providing “smartness” and thus additional value to each monitored/controlled …

Ad-iot: Anomaly detection of iot cyberattacks in smart city using machine learning

I Alrashdi, A Alqazzaz, E Aloufi… - 2019 IEEE 9th …, 2019 - ieeexplore.ieee.org
In recent years, the wide adoption of the modern Internet of Things (IoT) paradigm has led to
the invention of smart cities. Smart cities operate in real-world time to promote ease and …

A review of machine learning and deep learning techniques for anomaly detection in IoT data

R Al-amri, RK Murugesan, M Man, AF Abdulateef… - Applied Sciences, 2021 - mdpi.com
Anomaly detection has gained considerable attention in the past couple of years. Emerging
technologies, such as the Internet of Things (IoT), are known to be among the most critical …

Federated-learning-based anomaly detection for IoT security attacks

V Mothukuri, P Khare, RM Parizi… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is made up of billions of physical devices connected to the
Internet via networks that perform tasks independently with less human intervention. Such …

A graph neural network method for distributed anomaly detection in IoT

A Protogerou, S Papadopoulos, A Drosou, D Tzovaras… - Evolving Systems, 2021 - Springer
Recent IoT proliferation has undeniably affected the way organizational activities and
business procedures take place within several IoT domains such as smart manufacturing …

Unsupervised machine learning for network-centric anomaly detection in IoT

R Bhatia, S Benno, J Esteban, TV Lakshman… - Proceedings of the 3rd …, 2019 - dl.acm.org
Industry 4.0 holds the promise of greater automation and productivity but also introduces
new security risks to critical industrial control systems from unsecured devices and …

Classifying security attacks in IoT networks using supervised learning

C Ioannou, V Vassiliou - 2019 15th International conference on …, 2019 - ieeexplore.ieee.org
Machine learning models have long be proposed to detect the presence of unauthorized
activity within computer networks. They are used as anomaly detection techniques to detect …

Adriot: An edge-assisted anomaly detection framework against iot-based network attacks

R Li, Q Li, J Zhou, Y Jiang - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) has entered a stage of rapid development and increasing
deployment. Meanwhile, these low-power devices typically cannot support complex security …

Outlier detection approaches based on machine learning in the internet-of-things

J Jiang, G Han, L Shu, M Guizani - IEEE Wireless …, 2020 - ieeexplore.ieee.org
Outlier detection in the Internet of Things (IoT) is an essential challenge issue studied in
numerous fields, including fraud monitoring, intrusion detection, secure localization, trust …

A novel multi algorithm approach to identify network anomalies in the IoT using Fog computing and a model to distinguish between IoT and Non-IoT devices

RJ Alzahrani, A Alzahrani - Journal of Sensor and Actuator Networks, 2023 - mdpi.com
Botnet attacks, such as DDoS, are one of the most common types of attacks in IoT networks.
A botnet is a collection of cooperated computing machines or Internet of Things gadgets that …