Abstract
The Internet of Things (IoT) has emerged as a technology capable of connecting heterogeneous nodes/objects, such as people, devices, infrastructure, and makes our daily lives simpler, safer, and fruitful. Being part of a large network of heterogeneous devices, these nodes are typically resource-constrained and became the weakest link to the cyber attacker. Classical encryption techniques have been employed to ensure the data security of the IoT network. However, high-level encryption techniques cannot be employed in IoT devices due to the limitation of resources. In addition, node security is still a challenge for network engineers. Thus, we need to explore a complete solution for IoT networks that can ensure nodes and data security. The rule-based approaches and shallow and deep machine learning algorithms- branches of Artificial Intelligence (AI)- can be employed as countermeasures along with the existing network security protocols. This paper presented a comprehensive layer-wise survey on IoT security threats, and the AI-based security models to impede security threats. Finally, open challenges and future research directions are addressed for the safeguard of the IoT network.
| Original language | English |
|---|---|
| Article number | 9456954 |
| Pages (from-to) | 94668-94690 |
| Number of pages | 23 |
| Journal | IEEE Access |
| Volume | 9 |
| DOIs | |
| State | Published - 2021 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2013 IEEE.
Keywords
- Fuzzy logic
- IoT applications
- IoT protocols
- attack vector
- machine leaning
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering
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