BEYOND BOUNDARIES: FORTIFYING DATA SECURITY WITH CUTTING-EDGE CENSORED DATA MODELING AND ANTI-REGRESSION ADVANCEMENTS

Authors

  • Annisa Nugraha Department of Mathematics, Faculty of Mathematics and Natural Sciences, Andalas University, Indonesia

DOI:

https://doi.org/10.37547/history-crjh-05-01-04

Keywords:

Data Security, Censored Data Modeling, Anti-Regression

Abstract

In an era where data security is paramount, this study introduces a groundbreaking approach to fortify information integrity through advanced techniques in censored data modeling and anti-regression innovation. We delve into the intricacies of safeguarding sensitive insights, pushing the boundaries of conventional methodologies. The framework presented in this research not only enhances predictive accuracy but also ensures robust protection against potential threats, thus redefining the landscape of data security.

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References

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Published

2024-01-10

How to Cite

Annisa Nugraha. (2024). BEYOND BOUNDARIES: FORTIFYING DATA SECURITY WITH CUTTING-EDGE CENSORED DATA MODELING AND ANTI-REGRESSION ADVANCEMENTS. Current Research Journal of History, 5(01), 15–18. https://doi.org/10.37547/history-crjh-05-01-04