Security Threats and Artificial Intelligence Based Countermeasures for Internet of Things Networks: A Comprehensive Survey. Zaman, S., Mohammed A. Aseeri, Muhammad Raisuddin Ahmed, Risala Tasin Khan, M Shamim Kaiser, & Mufti Mahmud IEEE Access, 9:94668 – 94690, June, 2021.
doi  abstract   bibtex   
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.
@article{shakila_zaman_security_2021,
	title = {Security {Threats} and {Artificial} {Intelligence} {Based} {Countermeasures} for {Internet} of {Things} {Networks}: {A} {Comprehensive} {Survey}},
	volume = {9},
	doi = {10.1109/ACCESS.2021.3089681},
	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.},
	journal = {IEEE Access},
	author = {Shakila Zaman and {Mohammed A. Aseeri} and {Muhammad Raisuddin Ahmed} and {Risala Tasin Khan} and {M Shamim Kaiser} and {Mufti Mahmud}},
	month = jun,
	year = {2021},
	pages = {94668 -- 94690},
}

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