Skip to content
Research Article Open access CC BY 4.0

Attack and Anomaly Detection in IoT Networks using Machine Learning Techniques: A Review

Saad Hikmat Haji, Siddeeq Y. Ameen

Asian Journal of Research in Computer Science · pp. 30–46 · Published 2 Jun 2021

10.9734/ajrcos/2021/v9i230218

Abstract

The Internet of Things (IoT) is one of today's most rapidly growing technologies. It is a technology that allows billions of smart devices or objects known as "Things" to collect different types of data about themselves and their surroundings using various sensors. They may then share it with the authorized parties for various purposes, including controlling and monitoring industrial services or increasing business services or functions. However, the Internet of Things currently faces more security threats than ever before. Machine Learning (ML) has observed a critical technological breakthrough, which has opened several new research avenues to solve current and future IoT challenges. However, Machine Learning is a powerful technology to identify threats and suspected activities in intelligent devices and networks. In this paper, various ML algorithms have been compared in terms of attack detection and anomaly detection, following a thorough literature review on Machine Learning methods and the significance of IoT security in the context of various types of potential attacks. Furthermore, possible ML-based IoT protection technologies have been introduced.

Internet of Things (IoT) IoT attack machine learning anomaly detection

Cited by 108

IoT Network Anomaly Detection in Smart Homes Environment Using Hybrid Machine Learning Approach

J. Senthil, N. Karthikeyan, R. Senthilkumar · International Congress on Information and Communication Technology · 2025

Advanced Q-Learning-Based Dynamic Key Distribution for Secure Wireless Communication IoT Networks

Mohammed Aboud Kadhim, A. Ghaffoori, A. Hamad · Journal of Information Systems Engineering & Management · 2025

PETDA2C-EC: a privacy-enhancing technique to detect attacks against confidentiality in edge computing

Vipin Kumar, Vivek Kumar · Journal of Reliable Intelligent Environments · 2025

IoT Devices Attack Vectors and Its AI/ML Solutions

Happy, Rita Chhikara, Neeti Kashyap · 2025 International Conference on Next Generation Information System Engineering (NGISE) · 2025

Deep Learning Advancements in Anomaly Detection: A Comprehensive Survey

Haoqi Huang, Ping Wang, Jian-Hua Pei · IEEE Internet of Things Journal · 2025

Enhancing IoT Network Attack Detection with Ensemble Machine Learning and Efficient Feature Extraction

Mawahib Sharafeldin Adam Boush · Journal of Information Systems Engineering & Management · 2025

Cyber-physical systems security: A comprehensive review of anomaly detection techniques

Danial Abshari, Meera Sridhar · Internet of Things · 2025

Detecting Cyber Threats in IoT Networks: A Machine Learning Approach

Atheer Alaa Hammad, May Adnan Falih, Senan Ali Abd · International Journal of Computing and Digital Systems · 2025

Showing 104 of 108 known citations — external sources report more than can currently be individually listed.

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

108

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.