Quantitative security analysis using hypergraph based attack models

Abstract

Cloud Computing has revolutionized the way IT service are now offered to end users. It has become widespread and is also essential foundation to support current and future technologies of IT industry. This project tackles this challenge by introducing hypergraph-based entropy as a new way to analyze network security. Hypergraphs, unlike traditional models, can capture complex interactions between elements. The research offers a new traversal algorithm for attack scenarios, considers different levels of overlap when measuring uncertainty, and even proposes a method to identify and fix network vulnerabilities. Extensive testing confirms that strategically patching weaknesses based on this analysis significantly improves network security. Through comprehensive experimentation, the research validates the efficacy of these metrics, showcasing that strategic fortification informed by hypergraph entropy analysis substantially fortifies network resilience. Beyond furnishing practical tools for cybersecurity practitioners, this research lays the groundwork for future endeavors that fuse hypergraph theory with advanced mathematical frameworks to fortify cybersecurity defenses further.