IoT Cybersecurity Threats and Detection Mechanisms: A Review

Abstract

Now a day the internet of thing (IoT) grab the attention of many researchers and companies due to different direction of utilization. The cyber security of IoT become one of the aspects of the critical challenges. There are many intrusion detection systems (IDSs) to solve different issues of IoT-Cyber security threats. In this article, we review the state-of-the-art of IoT-IDS, focusing on the strategy that was devised and executed, the dataset that was utilized, the findings, and the assessment that was undertaken. Additionally, the surveyed articles undergo critical analysis and statements in order to give a thorough comparative review. Machine learning and deep learning methods, as well as new classification and feature selection methodologies, are studied and researched. Thus far, each technique has proved the capability of constructing very accurate intrusion detection models.

Keywords

• machine-learning
• deep-learning
• IoT-networks
• anomaly detection