Mathematical Models and Formulas for AI in Cybersecurity: a Hybrid Cloud Approach

EasyChair Preprint 15079

Abstract

The adoption of hybrid cloud environments introduces new security challenges that can be efficiently addressed using AI-driven solutions. To maximize the effectiveness of these AI systems, mathematical models and algorithms play a critical role in enhancing security measures, detecting threats, and optimizing system performance. This article explores the mathematical foundations behind AI algorithms in cybersecurity, focusing on their application to hybrid cloud infrastructures. Key models such as supervised learning, anomaly detection, encryption schemes, and optimization algorithms will be discussed to illustrate how mathematical formulations ensure robust cloud security

Keyphrases: Cryptography, Nash equilibrium, RSA Encryption, convex optimization, game theory, linear programming, resource optimization

@booklet{EasyChair:15079,
  author    = {Lincoln Whitelegge},
  title     = {Mathematical Models and Formulas for AI in Cybersecurity: a Hybrid Cloud Approach},
  howpublished = {EasyChair Preprint 15079},
  year      = {EasyChair, 2024}}