Deep Learning-Based Intrusion Detection System for Detecting IoT Botnet Attacks: A Review
Universiti Sains Malaysia · Najran University · +1 more institution
Abstract
The proliferation of Internet of Things (IoT) devices has brought about an increased threat of botnet attacks, necessitating robust security measures. In response to this evolving landscape, deep learning (DL)-based intrusion detection systems (IDS) have emerged as a promising approach for detecting and mitigating botnet activities in IoT environments. Therefore, this paper thoroughly reviews existing literature on botnet detection in the IoT using DL-based IDS. It consolidates and analyzes a wide range of research papers, highlighting key findings, methodologies, advancements, shortcomings, and challenges in the field. Additionally, we performed a qualitative comparison with existing surveys using…
Citation impact
- FWCI
- 74.59
- Percentile
- 100%
- References
- 102
Authors
8Topics & keywords
- Botnet
- Computer science
- Intrusion detection system
- Internet of Things
- Computer security
- Artificial intelligence
- Computer network
- The Internet