Research Preview

RQE Research

Advanced cybersecurity risk quantification methodologies and threat intelligence research

Quantitative Risk Modeling

Our proprietary risk quantification algorithms combine statistical analysis with real-world threat intelligence to provide accurate, financial-grade risk assessments.

Research Areas
  • Monte Carlo simulation for risk modeling
  • Bayesian inference in threat prediction
  • Machine learning for anomaly detection
  • Economic impact assessment methodologies

Threat Intelligence Studies

Comprehensive analysis of emerging cyber threats, attack vectors, and defensive strategies based on global threat landscape monitoring.

Data Sources
  • Global honeypot networks
  • Malware analysis laboratories
  • Industry collaboration frameworks
  • Academic research partnerships

Methodology Framework

Standardized approaches to risk quantification that comply with industry frameworks while providing actionable insights for security teams.

Framework Standards
  • FAIR (Factor Analysis of Information Risk)
  • NIST Cybersecurity Framework
  • ISO 27001/27005 risk management
  • OWASP risk rating methodology

Industry Collaboration

Partnerships with leading cybersecurity organizations, academic institutions, and industry consortiums to advance risk quantification science.

Partnerships
  • University research collaborations
  • Industry working groups
  • Government advisory committees
  • Open source security initiatives

Stay Informed

RQE research documentation and white papers are currently being prepared for publication. Get notified when they become available.

Research papers and methodologies will be published Q2 2025 | Academic collaborations welcome