FRANÇAIS
A showcase of ÉTS researchers’ publications and other contributions
SEARCH

State-of-the-art security schemes for the Internet of Underwater Things: A holistic survey

Adam, Nadir, Ali, Mansoor, Naeem, Faisal, Ghazy, Abdallah S. and Kaddoum, Georges. 2024. « State-of-the-art security schemes for the Internet of Underwater Things: A holistic survey ». IEEE Open Journal of the Communications Society, vol. 5. pp. 6561-6592.
Compte des citations dans Scopus : 5.

[thumbnail of Kaddoum-G-2024-29799.pdf]
Preview
PDF
Kaddoum-G-2024-29799.pdf - Published Version
Use licence: Creative Commons CC BY-NC-ND.

Download (6MB) | Preview

Abstract

With the growing interest that is being shown in marine resources, the concept of the Internet of Things (IoT) has been extended to underwater scenarios, which has given rise to the Internet of Underwater Things (IoUT). The IoUT encompasses a network of interconnected intelligent underwater devices that can be used to monitor underwater environments and support various applications, such as underwater exploration, disaster prevention, and environmental monitoring. Advances in underwater wireless communication and sensor technologies have propelled the IoUT concept forward. However, the IoUT faces significant challenges. The harsh and vast underwater environment makes information sensing particularly difficult and leads to insufficient or inaccurate data being collected. Additionally, underwater conditions like pressure variation, hydrological characteristics, temperature changes, water currents, and topography hinder conventional communication models and make data transmission difficult and inefficient. Security in IoUT networks is a critical concern due to hardware limitations and seawater channel imperfections. Constrained sensor nodes and spatial-temporal uncertainty introduced by node mobility further complicate security provisioning. This survey paper addresses these challenges by offering a comprehensive overview of IoUT security. The investigation thoroughly examines both traditional and classic machine learning techniques and focuses on deploying advanced technologies such as federated learning and digital twin. The study effectively addresses integration challenges and open issues and provides a roadmap for future directions to play a pivotal role in formulating robust security mechanisms for IoUT networks.

Item Type: Peer reviewed article published in a journal
Professor:
Professor
Kaddoum, Georges
Affiliation: Génie électrique
Date Deposited: 12 Nov 2024 16:46
Last Modified: 22 Nov 2024 15:08
URI: https://espace2.etsmtl.ca/id/eprint/29799

Actions (login required)

View Item View Item