Eurasian Journal of Mathematical Theory and Computer Sciences 5-jild 1-son (2025) · 26–35-betlar

STOCHASTIC PROGRAMMING UNDER PROBABILISTIC CONSTRAINTS AND ITS APPLICATION IN AUTHENTICATION SYSTEMS

Szucs, Veronika, Sulaymonov, Yusufbek

DOI: 10.5281/zenodo.14642706 · Manbada o'qish → · PDF (manba serverida)

Annotatsiya

Stochastic programming has emerged lately as an advanced mathematical method to develop a decision-making process under uncertainty. This work investigates its use in enhancing Multi-Factor Authentication systems by establishing a probability- maximized framework for dynamic authentication processes in real time. Tra- ditional MFA methods, though effective in reducing the risks of compromised credentials, usually have problems with user friction, lack of adaptability, and are vulnerable against advanced threats, including phishing and social engineer- ing. We propose a dynamic approach where stochastic models are integrated into MFA to adjust the authentication requirements based on real-time risk eval- uations and user behavior for better security and user experience.

Stochastic programming, multi-factor authenti- cation, cybersecurity, probability maximization.

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