Symmetric Encryption-Based Cloud Data Security Transmission System in Communication Networks
This paper addresses information transmission security issues within cloud computing security management platforms. Focusing on the symmetric encryption algorithm, it proposes a cloud computing data security transmission system, followed by model validation and simulation analysis. The key findings are as follows: (1) The use of a symmetric encryption algorithm ensures both user data security and the secure distribution of encryption keys. (2) The proposed encryption algorithm effectively conceals the distribution characteristics of explicit data, enhancing the information transmission security of the ship communication network. (3) The joint robust optimization algorithm outperforms other benchmark methods in terms of average safety rate. (4) The maximum speed between sampling nodes is calculated, revealing a speed difference of 0.3[Formula: see text]km/h between the embedded data and the original data. The average speed difference is 0.001[Formula: see text]km/h, with a speed change rate of only 0.01%. These results indicate that the algorithm proposed in this paper provides high secrecy and a large hidden capacity, making it suitable for secure information transmission in vehicle-to-network communications and from roadside intelligent facilities to cloud servers.
Authors
- Chao Yang (ORCID: https://orcid.org/0000-0003-4181-5356)
- Chaoliang Xu (ORCID: https://orcid.org/0009-0008-5956-4130)
- Xiaobo Wu (ORCID: https://orcid.org/0000-0001-5347-948X)
- Lige Tong (ORCID: https://orcid.org/0000-0001-6415-0372)
- Wen-Si Huang
Institutions
- Beijing Union University (CN)
- Electric Power Research Institute (US)
- North China Electric Power University (CN)
- State Grid Corporation of China (China) (CN)
- Northeast Electric Power University (CN)
- Shanghai Electric (China) (CN)
- Northeastern University (CN)
Publication Details
- Journal
- Journal of Circuits Systems and Computers
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1142/s0218126625502603
- Citations
- 1
- Primary Topic
- Internet of Things and AI
- Type
- article
- Field-Weighted Citation Impact
- 3.25