| Autor: |
Arumugam Maharajan, Parasuraman Kumar |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
International Journal of Naval Architecture and Ocean Engineering, Vol 16, Iss , Pp 100584- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2092-6782 |
| DOI: |
10.1016/j.ijnaoe.2024.100584 |
| Popis: |
The critical aspect in advancing global trade lies in ensuring security across marine trading systems. This research significantly contributes to monitoring ships by assessing operational performance parameters. These parameters are sensed through ship-attached sensors, and further transmitted to the cloud via an Internet of Things (IoT) Module. To optimize the efficiency of this data transfer to the cloud, the proposed work employs a Whale Optimization Algorithm-based Radial Basis Function Neural Network (WOA-RBFNN). The utilization of this algorithm enhances the overall effectiveness of the system. Furthermore, to address security concerns, a 128-bit Two Fish Algorithm-based key management is introduced, providing enhanced data protection. This dual-focus approach not only optimizes the efficiency of data transmission but also fortifies the system against potential cyber threats. These enhancements collectively contribute to the successful and secure transmission of information to the cloud advancing the security and efficiency of marine trading systems. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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