- Title
- Bio-inspired network security for 5G-enabled IoT applications
- Creator
- Saleem, Kashif; Alabduljabbar, Ghadah; Alrowais, Nouf; Al-Muhtadi, Jalal; Imran, Muhammad; Rodrigues, Joel
- Date
- 2020
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/184147
- Identifier
- vital:16452
- Identifier
-
https://doi.org/10.1109/ACCESS.2020.3046325
- Identifier
- ISBN:2169-3536
- Abstract
- Every IPv6-enabled device connected and communicating over the Internet forms the Internet of things (IoT) that is prevalent in society and is used in daily life. This IoT platform will quickly grow to be populated with billions or more objects by making every electrical appliance, car, and even items of furniture smart and connected. The 5th generation (5G) and beyond networks will further boost these IoT systems. The massive utilization of these systems over gigabits per second generates numerous issues. Owing to the huge complexity in large-scale deployment of IoT, data privacy and security are the most prominent challenges, especially for critical applications such as Industry 4.0, e-healthcare, and military. Threat agents persistently strive to find new vulnerabilities and exploit them. Therefore, including promising security measures to support the running systems, not to harm or collapse them, is essential. Nature-inspired algorithms have the capability to provide autonomous and sustainable defense and healing mechanisms. This paper first surveys the 5G network layer security for IoT applications and lists the network layer security vulnerabilities and requirements in wireless sensor networks, IoT, and 5G-enabled IoT. Second, a detailed literature review is conducted with the current network layer security methods and the bio-inspired techniques for IoT applications exchanging data packets over 5G. Finally, the bio-inspired algorithms are analyzed in the context of providing a secure network layer for IoT applications connected over 5G and beyond networks.
- Publisher
- IEEE
- Relation
- IEEE access Vol. 8, no. (2020), p. 1-1
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright @ IEEE
- Rights
- Open Access
- Subject
- 40 Engineering; 46 Information and Computing Sciences; 5G mobile communication; 5th Generation Network; Algorithms; Artificial Intelligence; Authentication; Biological; Computer network reliability; Electric appliances; Genetic algorithms; Industrial applications; Internet of Things; IP (Internet Protocol); Literature reviews; Network layer; Network security; Packets (communication); Routing; Security; the Internet of Things; Wireless networks; Wireless Sensor Networks
- Full Text
- Reviewed
- Funder
- The authors extend their appreciation to the Deputyship for Research and Innovation, ‘‘Ministry of Education’’ in Saudi Arabia for funding this research work through the Project no. (IFKSURP-109).
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