┌─────────────────────────────────────────────────────────────────────────────┐
│                    RANSOMWARE ATTACK LIFECYCLE                            │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    RECONNAISSANCE                                   │   │
│  │  Identify targets, vulnerabilities                                 │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                    │                                        │
│                                    v                                        │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    DELIVERY                                         │   │
│  │  Phishing, exploit, remote access                                  │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                    │                                        │
│                                    v                                        │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    EXECUTION                                        │   │
│  │  Deploy ransomware                                                │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                    │                                        │
│                                    v                                        │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    ENCRYPTION                                       │   │
│  │  Encrypt files and systems                                         │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                    │                                        │
│                                    v                                        │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    RANSOM DEMAND                                    │   │
│  │  Demand payment for decryption key                                 │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

# ===================================================================
# MODULE 5, LESSON 8: EMERGING THREATS AND FUTURE TRENDS
# ===================================================================

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime, timedelta
import warnings
warnings.filterwarnings('ignore')

print("="*70)
print("EMERGING THREATS AND FUTURE TRENDS IN CYBERSECURITY")
print("="*70)

# ----------------------------------------------------------------
# PART A: EMERGING THREAT LANDSCAPE
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART A: Emerging Threat Landscape")
print("-"*60)

# Define emerging threats
emerging_threats = pd.DataFrame({
    'Threat': [
        'AI-Powered Attacks',
        'Ransomware-as-a-Service',
        'Supply Chain Attacks',
        'Deepfakes',
        'Quantum Attacks',
        'IoT Attacks',
        'Cloud Attacks',
        'Generative AI Attacks'
    ],
    'Likelihood (1-5)': [5, 4, 4, 3, 2, 4, 4, 4],
    'Impact (1-5)': [5, 5, 5, 4, 5, 3, 5, 4],
    'Timeline (years)': [1, 1, 2, 2, 5, 2, 1, 1],
    'Banking Impact': ['High', 'High', 'High', 'Medium', 'Critical', 'Medium', 'High', 'High']
})

print("Emerging Threat Landscape:")
print(emerging_threats.to_string(index=False))

# Visualise
fig, ax = plt.subplots(figsize=(10, 6))
scatter = ax.scatter(emerging_threats['Likelihood (1-5)'], emerging_threats['Impact (1-5)'], 
                     s=emerging_threats['Timeline (years)'] * 50, alpha=0.7)
for i, row in emerging_threats.iterrows():
    ax.annotate(row['Threat'], (row['Likelihood (1-5)'] + 0.1, row['Impact (1-5)'] + 0.1))
ax.set_xlabel('Likelihood (1-5)')
ax.set_ylabel('Impact (1-5)')
ax.set_title('Emerging Threats: Likelihood vs Impact (size = timeline)')
ax.grid(True, alpha=0.3)
plt.tight_layout()
plt.savefig('emerging_threats.png', dpi=300, bbox_inches='tight')
plt.show()
print("Emerging threats visualisation saved as 'emerging_threats.png'")

# ----------------------------------------------------------------
# PART B: AI-POWERED ATTACK SCENARIOS
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART B: AI-Powered Attack Scenarios")
print("-"*60)

ai_attacks = pd.DataFrame({
    'Attack Scenario': [
        'AI-Enhanced Phishing',
        'Deepfake Fraud',
        'Automated Credential Attacks',
        'Adversarial AI',
        'AI-Driven Malware'
    ],
    'Attack Vectors': [
        'Email, SMS, Social Media',
        'Voice, Video, Identity',
        'API, Web, Authentication',
        'AI Models, Systems',
        'Network, Endpoints'
    ],
    'Complexity (1-5)': [3, 5, 4, 5, 5],
    'Probability (1-5)': [5, 3, 5, 3, 2],
    'Mitigation': [
        'AI Detection, Training',
        'Deepfake Detection',
        'MFA, Zero Trust',
        'Adversarial Training',
        'Endpoint Protection, Zero Trust'
    ]
})

print("AI-Powered Attack Scenarios:")
print(ai_attacks.to_string(index=False))

# ----------------------------------------------------------------
# PART C: QUANTUM RESISTANCE READINESS
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART C: Quantum Resistance Readiness")
print("-"*60)

quantum_readiness = pd.DataFrame({
    'Area': ['Encryption', 'Digital Signatures', 'Key Management', 'Random Number Generation', 'Cryptographic Protocols'],
    'Current Algorithm': ['RSA-2048', 'RSA-2048', 'RSA-2048', 'PRNG', 'RSA'],
    'Quantum Risk': ['High', 'High', 'High', 'Medium', 'High'],
    'Post-Quantum Alternative': ['CRYSTALS-Kyber', 'CRYSTALS-Dilithium', 'Hybrid', 'Quantum-RNG', 'KEM'],
    'Status': ['Assessment', 'Assessment', 'Assessment', 'Assessment', 'Assessment']
})

print("Quantum Resistance Readiness:")
print(quantum_readiness.to_string(index=False))

# ----------------------------------------------------------------
# PART D: RANSOMWARE RESILIENCE MATURITY
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART D: Ransomware Resilience Maturity")
print("-"*60)

ransomware_resilience = pd.DataFrame({
    'Capability': ['Backup and Recovery', 'Endpoint Protection', 'Network Segmentation', 
                   'Zero Trust', 'Incident Response', 'Employee Training'],
    'Current Score (1-5)': [4, 3, 2, 2, 3, 3],
    'Target Score (1-5)': [5, 5, 5, 5, 5, 5],
    'Priority': ['High', 'High', 'High', 'High', 'High', 'Medium']
})

print("Ransomware Resilience Maturity:")
print(ransomware_resilience.to_string(index=False))

# Visualise
fig, ax = plt.subplots(figsize=(10, 6))
capabilities = ransomware_resilience['Capability'].tolist()
current = ransomware_resilience['Current Score (1-5)'].tolist()
target = ransomware_resilience['Target Score (1-5)'].tolist()

x = np.arange(len(capabilities))
width = 0.35

ax.barh(x - width/2, current, width, label='Current', color='blue', alpha=0.7)
ax.barh(x + width/2, target, width, label='Target', color='green', alpha=0.7)

ax.set_yticks(x)
ax.set_yticklabels(capabilities)
ax.set_xlabel('Maturity Score (1-5)')
ax.set_title('Ransomware Resilience Maturity')
ax.legend()
ax.grid(True, alpha=0.3, axis='x')

plt.tight_layout()
plt.savefig('ransomware_resilience.png', dpi=300, bbox_inches='tight')
plt.show()
print("Ransomware resilience visualisation saved as 'ransomware_resilience.png'")

# ----------------------------------------------------------------
# PART E: CYBERSECURITY FUTURE METRICS
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART E: Cybersecurity Future Metrics")
print("-"*60)

future_metrics = pd.DataFrame({
    'Metric': [
        'AI Threat Detection Rate',
        'Quantum Readiness Score',
        'Ransomware Resilience Score',
        'Attack Surface Reduction',
        'Zero Trust Adoption',
        'Deepfake Detection Accuracy',
        'Supply Chain Security Score',
        'Cyber Insurance Coverage'
    ],
    'Current Value': [
        '65%',
        '40/100',
        '58/100',
        '30%',
        '45%',
        '72%',
        '55/100',
        '$50M'
    ],
    'Target Value': [
        '> 95%',
        '> 80/100',
        '> 85/100',
        '> 70%',
        '> 90%',
        '> 95%',
        '> 85/100',
        '$200M'
    ],
    'Status': ['🟡', '🔴', '🔴', '🔴', '🔴', '🟡', '🔴', '🟡']
})

print("Cybersecurity Future Metrics:")
print(future_metrics.to_string(index=False))

# ----------------------------------------------------------------
# PART F: FUTURE-READY CYBERSECURITY ROADMAP
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART F: Future-Ready Cybersecurity Roadmap")
print("-"*60)

roadmap = {
    "Phase 1 (0-12 months) – Foundation": {
        "Focus": "Build resilience against current and emerging threats.",
        "Activities": [
            "Implement AI-powered threat detection.",
            "Deploy zero-trust architecture.",
            "Develop ransomware resilience strategy.",
            "Establish quantum readiness plan."
        ],
        "Success Metrics": ["Zero trust adoption > 60%", "AI detection rate > 80%"]
    },
    "Phase 2 (12-24 months) – Scale": {
        "Focus": "Scale emerging threat capabilities.",
        "Activities": [
            "Implement deepfake detection.",
            "Deploy quantum-resistant cryptography.",
            "Build AI defence capabilities.",
            "Enhance supply chain security."
        ],
        "Success Metrics": ["Quantum readiness > 60%", "Deepfake detection > 90%"]
    },
    "Phase 3 (24-36 months) – Advanced": {
        "Focus": "Advanced threat protection.",
        "Activities": [
            "Implement predictive AI security.",
            "Deploy automated threat response.",
            "Build adversarial AI defences.",
            "Achieve industry-leading resilience."
        ],
        "Success Metrics": ["Automated response > 80%", "Industry-leading security"]
    },
    "Phase 4 (36+ months) – Leadership": {
        "Focus": "Industry leadership in cybersecurity.",
        "Activities": [
            "Implement self-healing security.",
            "Build AI-driven security operations.",
            "Achieve quantum readiness.",
            "Establish security culture."
        ],
        "Success Metrics": ["Quantum readiness > 90%", "Industry leadership"]
    }
}

for phase, details in roadmap.items():
    print(f"\n{phase}:")
    print(f"  Focus: {details['Focus']}")
    print("  Activities:")
    for activity in details['Activities']:
        print(f"    • {activity}")
    print("  Success Metrics:")
    for metric in details['Success Metrics']:
        print(f"    • {metric}")

# ----------------------------------------------------------------
# PART G: SUMMARY AND RECOMMENDATIONS
# ----------------------------------------------------------------

print("\n" + "="*70)
print("PART G: Summary and Recommendations")
print("="*70)

print("""
Emerging Threats and Future Trends – Key Takeaways:

1. Emerging threats: AI-powered attacks, ransomware-as-a-service, supply chain, deepfakes, quantum.
2. AI-powered attacks include AI-enhanced phishing, deepfakes, automated attacks, adversarial AI.
3. Quantum computing threatens current cryptography; quantum-resistant algorithms are being developed.
4. Ransomware resilience requires backup, endpoint protection, segmentation, zero trust.
5. Key metrics: AI detection rate, quantum readiness, ransomware resilience, deepfake detection.
6. Future-ready strategy: foundation → scale → advanced → leadership.

Recommendations:
  - Implement AI-powered threat detection.
  - Develop quantum-resistant cryptography strategy.
  - Build ransomware resilience capabilities.
  - Deploy zero-trust architecture.
  - Invest in deepfake detection.
  - Continuously assess and adapt to emerging threats.
""")

print("="*70)
print("END OF LESSON 8 – MODULE 5")
print("="*70)