A State of the Art Survey of Machine Learning Algorithms for IoT Security
Alan Fuad Jahwar, Subhi R. M. Zeebaree
Asian Journal of Research in Computer Science · pp. 12–34 · Published 16 Jun 2021
10.9734/ajrcos/2021/v9i430226Abstract
The Internet of Things (IoT) is a paradigm shift that enables billions of devices to connect to the Internet. The IoT's diverse application domains, including smart cities, smart homes, and e-health, have created new challenges, chief among them security threats. To accommodate the current networking model, traditional security measures such as firewalls and Intrusion Detection Systems (IDS) must be modified. Additionally, the Internet of Things and Cloud Computing complement one another, frequently used interchangeably when discussing technical services and collaborating to provide a more comprehensive IoT service. In this review, we focus on recent Machine Learning (ML) and Deep Learning (DL) algorithms proposed in IoT security, which can be used to address various security issues. This paper systematically reviews the architecture of IoT applications, the security aspect of IoT, service models of cloud computing, and cloud deployment models. Finally, we discuss the latest ML and DL strategies for solving various security issues in IoT networks.
Cited by 7
Umer Farooq, Noshina Tariq, Muhammad Asim · Journal of Parallel and Distributed Computing · 2022
Vaidehi Amey Dinkar, Priyank D. Doshi · Lecture Notes in Networks and Systems · 2026
M. Wasim Abbas Ashraf, Arvind R. Singh, A. Pandian · Scientific Reports · 2024
B Satheesh Kumar, Putta Srivani, D Kalyani · 2025 7th International Conference on Innovative Data Communication Technologies and Application (ICIDCA) · 2025
Nassiba Wafa Abderrahim, Amina Benosman · Engineering Research Express · 2025
Juan Ignacio Iturbe Araya, Helena Rifà-Pous · Internet of Things · 2023
Shakir M. Abas, Omer Mohammed Salih Hassan, Imad Manaf Ali · 2022 4th International Conference on Advanced Science and Engineering (ICOASE) · 2022
Related research
- Automatic Segmentation of Organ at Risk in Head and Neck Cancer CT Images Using Medical Open Network for Artificial Intelligence (MONAI) with Deep Learning Techniques — shares topic coverage
- Diagnostic Accuracy of Artificial Intelligence for Breast Cancer Detection: A Systematic Review — shares topic coverage
- Leveraging Deep Learning Algorithms for Predicting Power Outages and Detecting Faults: A Review — shares topic coverage
- Bridging Prenatal Diagnostics and AI: A Systematic Review and Meta-Analysis of the Efficacy of Advanced Algorithms in Identifying Congenital Fetal Abnormalities — shares topic coverage
- Applications of Deep Learning in Predicting the Risk of Metabolic Syndrome from Lifestyle and Behavioral Factors: A Scoping Review — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
7
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.