Abstract :

As The Volume Of Transmitting And Storing Information Explodes, Secure Sharing Of The Data Has Become An Utmost Priority In Business And Academic Circles. Although Very Robust, Traditional Cryptographic Systems Tend To Have Scaling And Computational Performance Drawbacks. The Paper At Hand Discusses A New Cryptographic System That Uses Matrix Factorization Method To Provide Secure And Efficient Sharing Of Data. In Exploiting The Mathematical Difficulty Of Matrix Decomposition E.g. Singular Value Decomposition (SVD) And Non-negative Matrix Factorization (NMF), The Proposed Approach Provides A Multi-layered Encryption Framework That Projects Data In The Form Of Latent Factor Matrices Prior To Transmission. These Factor Matrices, Which Cannot Be Understood On Their Own, Provide A Natural Degree Of Obfuscation. Scheme Performance Is Assessed By Means Of Simulated Data Sharing Scenarios And Compared To That Of RSA And AES Standards. The Conducted Experiments Have Shown That The Suggested Technique Ensures A High Level Of Security And Enhances The Computational Efficiency, Especially In The Case Of Large-scale Data Systems. This Work Forms The Foundation Of Scalable, Mathematically Proven Data Exchange Protocols In Cloud (and Edge-computing) Systems Of The Future. Keywords— Matrix Factorization, Cryptography, Data Security, SVD, Secure Data Sharing, Encryption, Decryption, Cloud Security, Latent Matrix Encryption, Homomorphic Features.

Published:

25-9-2025

Issue:

Vol. 25 No. 9 (2025)

Page Nos:

616-623

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite