A computer network communication data encryption method based on improved MD5 algorithm

Yuanyuan Huang; Zhu Huang

doi:10.1117/12.3038028

22 August 2024 A computer network communication data encryption method based on improved MD5 algorithm

Yuanyuan Huang, Zhu Huang

Author Affiliations +

Proceedings Volume 13228, Fifth International Conference on Computer Communication and Network Security (CCNS 2024); 132280N (2024) https://doi.org/10.1117/12.3038028
Event: Fifth International Conference on Computer Communication and Network Security (CCNS 2024), 2024, Guangzhou, China

Abstract

The traditional communication data encryption methods rely on complete time series to extract encryption features, making them susceptible to data noise and resulting in high packet loss rates. To address these issues, this study introduces an enhanced MD5 algorithm for encrypting network communication data. Initially, a Huffman single item reassembly encryption structure is established to create a deployment of multi-objective fine-grained encryption nodes. Subsequently, a sliding homomorphic mixed encryption model is developed, along with derived network communication encryption instructions. This is followed by the use of overlapping deep learning algorithms to achieve mixed encryption of network communication data. Compared to encryption methods based on ring topology and VPN technology, the proposed encryption structure is more flexible, variable, and exhibits dynamic accounting verification characteristics. The findings indicate that there are fewer encryption discrepancies in practical applications, and the data maintains higher stability during the mixed encryption process.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuanyuan Huang and Zhu Huang "A computer network communication data encryption method based on improved MD5 algorithm", Proc. SPIE 13228, Fifth International Conference on Computer Communication and Network Security (CCNS 2024), 132280N (22 August 2024); https://doi.org/10.1117/12.3038028

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE