Vectors and Victims - Analyzing Vulnerabilities Through Disease Models

Overview

Explore vulnerability analysis using disease models to understand attack vectors and potential victims in cybersecurity, drawing insights from epidemiology.

Syllabus

• Introduction to Vulnerability Analysis
Overview of cybersecurity vulnerabilities
Importance of vulnerability analysis in cybersecurity
• Basics of Disease Models
Key concepts in epidemiology
Overview of common disease models (SIR, SEIR, etc.)
• Mapping Disease Models to Cybersecurity
Analogy between disease models and cybersecurity threats
Attack vectors and digital "infection" paths
• Biological vs. Digital Infection
Case studies of biological diseases and their digital equivalents
Dynamics of infection spread in both domains
• Vulnerability Identification and Assessment
Techniques for identifying vulnerabilities in cyber systems
Comparing and contrasting with biological vulnerability assessment
• Understanding Attack Vectors
Identification and analysis of attack vectors in cybersecurity
Drawing parallels with transmission modes in epidemiology
• Profiling Potential Victims
Identifying high-risk targets in a network
Epidemiological insights into profiling victims
• Modeling and Simulation Techniques
Introduction to modeling tools used in disease and cybersecurity
Practical simulation exercises comparing both domains
• Case Study: Analyzing a Cyber Epidemic
Breakdown of a real-world cyber attack resembling an epidemic
Step-by-step analysis using disease model frameworks
• Strategies for Mitigation and Risk Reduction
Prevention methods in both healthcare and cybersecurity
Mitigation techniques and response plans
• Future Directions in Cybersecurity Through Epidemiology
Upcoming trends and research areas
Potential for cross-disciplinary collaboration
• Course Summary and Final Project
Overview of key learnings
Final project: Develop a comprehensive analysis of a hypothetical cyber attack using disease modeling techniques.

Subjects

Conference Talks