Cyberwar Clock Framework

A Novel Predictive Framework for Global Cyber Conflict Risk Assessment

Go to V2
12
3
6
9
12
3
6
9
CWCS Range Clock Time Risk Phase
0.0-2.5 11 PM – 1 AM Latent
2.6-5.0 2 AM – 5 AM Emerging
5.1-7.5 6 AM – 9 AM Active
7.6-10.0 10 AM – 12 PM Critical

Core Formula

CWCS = αTES + βTAF + γGTI - δDCI
α = 0.40 | β = 0.30 | γ = 0.20 | δ = 0.10
Weighting Coefficients (Delphi Method, n=42, κ=0.81):
• Threat Evolution (α): 40% - Primary driver
• Technology Acceleration (β): 30% - Disruptive factor
• Geopolitical Tension (γ): 20% - Context amplifier
• Defensive Countermeasures (δ): 10% - Risk mitigation
Threat Evolution Score (TES)
α = 0.40
Quantifies maturation of cyber threats through sophistication, impact, and defensive capabilities with temporal weighting.
• Sophistication: MITRE ATT&CK techniques + zero-days
• Impact: Economic damage + infrastructure downtime
• Defenses: Detection rate × patch adoption
• Temporal decay: λ = 0.15 (recent threats prioritized)
Technology Acceleration Factor (TAF)
β = 0.30
Captures destabilizing impact of emerging technologies on cyber conflict landscape.
• AI Net Threat: Offensive vs Defensive AI capabilities
• Quantum Risk: Q-probability + data harvesting
• Autonomous Malware: Gen4 prevalence × propagation
• ICS/IoT vulnerabilities + Deepfakes + QAI convergence
Geopolitical Tension Index (GTI)
γ = 0.20
Measures cyber-instability through interstate friction and state/non-state actor dynamics.
• Arms Race: Cyber budgets × capability demonstrations
• Sanctions: Cyber-related sanctions × severity
• Military Posture: National cyber strategy analysis
• Treaties compliance + Safe havens + Non-state activity
Defensive Countermeasure Index (DCI)
δ = -0.10
Evaluates global capacity to mitigate cyber threats through technical defenses and diplomacy.
• Post-Quantum Crypto: NIST algorithm adoption
• AI Defenses: SOC tool adoption × accuracy
• Diplomacy: Ratified norms + ongoing initiatives
• Infrastructure Hardening: CISA resilience metrics

Data Sources & Intelligence Feeds

Threat Intelligence

MITRE ATT&CK Framework Adversarial tactics, techniques, and procedures (TTPs)
Microsoft Security Intelligence AI-powered threat detection and phishing success rates
CrowdStrike Threat Intelligence Mean time to detection (MTTD) and defensive AI metrics
Dragos ICS Threat Database Industrial control system vulnerabilities and attack patterns
Chainalysis Crypto Crime Report Ransomware payments and cryptocurrency transaction analysis

Geopolitical Intelligence

SIPRI Military Expenditure Database Cyber-related military budgets and capability investments
NATO Cyber Defense Reports Alliance cyber posture and threat assessments
UN OEWG Cyber Norms International cyber governance and treaty compliance
Europol & INTERPOL Assessments Cybercriminal safe havens and law enforcement cooperation
National Cyber Strategy Documents Offensive/defensive doctrine analysis via content analysis

Technology Indicators

NIST Post-Quantum Standards Quantum-resistant cryptography adoption metrics
Patent & Research Databases Quantum-AI convergence trends and innovation tracking
Financial Times Deepfake Studies AI deception success rates in controlled environments
Enterprise Security Surveys AI-based SOC tool adoption and false positive rates
Quantum Computing Roadmaps Expert assessments of cryptographically relevant quantum computers

Critical Infrastructure

CISA Infrastructure Assessments Critical infrastructure resilience and hardening metrics
ICS-CERT Incident Reports Industrial control system attack frequency and impact
Economic Impact Databases Cyber incident financial damage assessments (USD billions)
Downtime Monitoring Services Critical infrastructure service availability and outage duration
IoT Security Assessments Consumer and industrial IoT vulnerability prevalence

Data Quality & Validation

Expert Validation: 42-expert Delphi process (κ = 0.81) for weight determination
Update Frequency: Real-time feeds for threat intelligence, monthly for geopolitical indicators
Normalization: All metrics scaled to [0,10] for consistent cross-domain comparison
Temporal Weighting: Exponential decay (λ = 0.15) prioritizes recent threat evolution
Methodological Innovation: The CWC framework advances beyond traditional risk models (MITRE ATT&CK, Diamond Model) by incorporating temporal weighting, quantum/AI disruption factors, non-state actor dynamics, and defensive mitigation effects. Grounded in complex systems theory, it treats cyber conflict as an emergent phenomenon shaped by adversarial adaptation, technological acceleration, and geopolitical friction.