┌─────────────────────────────────────────────────────────────────────────────┐
│                    CORE PRIVACY PRINCIPLES                                  │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  1. LAWFULNESS, FAIRNESS, TRANSPARENCY                                     │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Process data lawfully and fairly                                  │   │
│  │ • Be transparent about data processing                            │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  2. PURPOSE LIMITATION                                                     │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Collect data for specified, explicit, legitimate purposes         │   │
│  │ • Do not use data for incompatible purposes                         │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  3. DATA MINIMISATION                                                      │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Collect only necessary data                                       │   │
│  │ • Limit data retention                                              │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  4. ACCURACY                                                                │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Keep data accurate and up to date                                 │   │
│  │ • Correct or delete inaccurate data                                 │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  5. STORAGE LIMITATION                                                     │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Store data only as long as necessary                              │   │
│  │ • Delete or anonymise when no longer needed                        │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  6. INTEGRITY AND CONFIDENTIALITY                                          │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Protect data against unauthorised access                         │   │
│  │ • Ensure technical and organisational security                     │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────────────────┐
│                    BLOCKCHAIN PRIVACY CHALLENGES                            │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  1. IMMUTABILITY                                                           │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Data on blockchain cannot be modified or deleted                  │   │
│  │ • Conflicts with "right to be forgotten" (GDPR Art 17)             │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  2. PSEUDONYMITY                                                           │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Wallet addresses are pseudonymous but not anonymous               │   │
│  │ • Transactions are publicly visible                                 │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  3. DATA MINIMISATION                                                      │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Blockchain stores data permanently                               │   │
│  │ • Difficult to limit data retention                                │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  4. CROSS-BORDER DATA TRANSFERS                                            │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Blockchain data is distributed globally                           │   │
│  │ • Difficult to comply with jurisdiction-specific rules             │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  5. TRANSPARENCY VS PRIVACY                                               │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │ • Blockchain is designed for transparency                          │   │
│  │ • Privacy regulations require confidentiality                      │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

# ===================================================================
# MODULE 5, LESSON 4: DATA PRIVACY AND PROTECTION
# ===================================================================

import hashlib
import time
import json
from typing import Dict, List, Optional
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import warnings
warnings.filterwarnings('ignore')

print("="*70)
print("DATA PRIVACY AND PROTECTION")
print("="*70)

# ----------------------------------------------------------------
# PART A: DATA PRIVACY COMPLIANCE SIMULATION
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART A: Data Privacy Compliance Simulation")
print("-"*60)

class DataPrivacyManager:
    """
    Simulated data privacy compliance manager.
    """
    def __init__(self):
        self.user_data = {}
        self.consent_records = {}
        self.data_access_logs = []
        self.deletion_requests = []
    
    def collect_data(self, user_id: str, data: Dict, purpose: str, consent: bool) -> bool:
        """Collect user data with consent."""
        if not consent:
            print(f"Data collection for {user_id} requires consent")
            return False
        
        self.user_data[user_id] = {
            'data': data,
            'purpose': purpose,
            'collected_at': time.time(),
            'retention_period': 365  # days
        }
        self.consent_records[user_id] = {
            'granted_at': time.time(),
            'purpose': purpose,
            'status': 'Active'
        }
        print(f"Data collected for user {user_id}")
        return True
    
    def access_data(self, user_id: str, requester: str) -> Optional[Dict]:
        """Simulate data access request."""
        if user_id not in self.user_data:
            print(f"User {user_id} not found")
            return None
        
        # Log access
        self.data_access_logs.append({
            'user': user_id,
            'requester': requester,
            'timestamp': time.time()
        })
        
        print(f"Data access for {user_id} by {requester}")
        return self.user_data[user_id]['data']
    
    def delete_data(self, user_id: str) -> bool:
        """Simulate data deletion (right to be forgotten)."""
        if user_id not in self.user_data:
            print(f"User {user_id} not found")
            return False
        
        # Anonymise rather than delete for blockchain data
        self.user_data[user_id]['data']['anonymised'] = True
        self.user_data[user_id]['data']['original'] = '**[DELETED]**'
        self.deletion_requests.append({
            'user': user_id,
            'timestamp': time.time(),
            'status': 'Completed'
        })
        
        print(f"Data deleted for user {user_id}")
        return True
    
    def get_consent_status(self, user_id: str) -> Dict:
        """Check consent status."""
        if user_id not in self.consent_records:
            return {'status': 'No Consent Record'}
        return self.consent_records[user_id]
    
    def get_compliance_report(self) -> Dict:
        """Generate compliance metrics."""
        return {
            'total_users': len(self.user_data),
            'consent_given': len([c for c in self.consent_records.values() if c['status'] == 'Active']),
            'data_access_requests': len(self.data_access_logs),
            'deletion_requests': len(self.deletion_requests)
        }

# Simulate privacy compliance
privacy = DataPrivacyManager()

print("Data Privacy Compliance Simulation:")

# Collect data with consent
privacy.collect_data('user_001', 
                     {'name': 'Alice Johnson', 'email': 'alice@example.com', 'wallet': '0x123...'},
                     'KYC Verification', True)

privacy.collect_data('user_002',
                     {'name': 'Bob Smith', 'email': 'bob@example.com', 'wallet': '0x456...'},
                     'KYC Verification', False)  # No consent

# Access data
privacy.access_data('user_001', 'Compliance Officer')
privacy.access_data('user_001', 'Auditor')

# Delete data
privacy.delete_data('user_001')

# Compliance report
report = privacy.get_compliance_report()
print(f"\nCompliance Report:")
print(f"  Total Users: {report['total_users']}")
print(f"  Consent Given: {report['consent_given']}")
print(f"  Data Access Requests: {report['data_access_requests']}")
print(f"  Deletion Requests: {report['deletion_requests']}")

# ----------------------------------------------------------------
# PART B: GDPR PRINCIPLES CHECKLIST
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART B: GDPR Principles Checklist")
print("-"*60)

gdpr_checklist = {
    "Lawfulness, Fairness, Transparency": [
        "Do you have a lawful basis for processing?",
        "Is data processing fair to data subjects?",
        "Is processing transparent and clearly communicated?"
    ],
    "Purpose Limitation": [
        "Are purposes specified and legitimate?",
        "Is data processed only for specified purposes?",
        "Are incompatible uses prohibited?"
    ],
    "Data Minimisation": [
        "Is data adequate, relevant, and limited?",
        "Is only necessary data collected?",
        "Is excess data avoided?"
    ],
    "Accuracy": [
        "Is data accurate and up to date?",
        "Are inaccurate data corrected or deleted?",
        "Is accuracy regularly verified?"
    ],
    "Storage Limitation": [
        "Is data stored only as long as necessary?",
        "Is retention period defined?",
        "Are deletion processes in place?"
    ],
    "Integrity and Confidentiality": [
        "Is data secure?",
        "Are technical and organisational measures in place?",
        "Is unauthorised access prevented?"
    ]
}

for principle, questions in gdpr_checklist.items():
    print(f"\n{principle.upper()}:")
    for q in questions:
        print(f"  • {q}")

# ----------------------------------------------------------------
# PART C: PRIVACY AND BLOCKCHAIN COMPARISON
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART C: Privacy and Blockchain Comparison")
print("-"*60)

privacy_comparison = {
    'Feature': ['Data Modification', 'Data Deletion', 'Data Sharing', 'Privacy Control', 'Auditability'],
    'Traditional Database': ['Easy', 'Easy', 'Controlled', 'Admin-driven', 'Limited'],
    'Blockchain (Public)': ['Impossible', 'Impossible', 'Public (all)', 'Pseudonymous', 'Full'],
    'Blockchain (Private)': ['Controlled', 'Controlled', 'Controlled', 'Admin-driven', 'Full']
}

privacy_df = pd.DataFrame(privacy_comparison)
print(privacy_df.to_string(index=False))

# ----------------------------------------------------------------
# PART D: PRIVACY-ENHANCING TECHNOLOGIES
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART D: Privacy-Enhancing Technologies")
print("-"*60)

pet_data = {
    'Technology': ['Zero-Knowledge Proofs', 'Differential Privacy', 'Secure Multiparty Computation', 'Homomorphic Encryption'],
    'Description': [
        'Prove knowledge without revealing information',
        'Add noise to protect individual data',
        'Collaborative computation without revealing inputs',
        'Compute on encrypted data'
    ],
    'Privacy Level': ['Very High', 'High', 'Very High', 'Very High'],
    'Complexity': ['Medium', 'Low', 'High', 'Very High'],
    'Use Case': ['Private transactions', 'Analytics', 'Collaborative computation', 'Secure data processing']
}

pet_df = pd.DataFrame(pet_data)
print(pet_df.to_string(index=False))

# ----------------------------------------------------------------
# PART E: SUMMARY AND RECOMMENDATIONS
# ----------------------------------------------------------------

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

print("""
Data Privacy and Protection – Key Takeaways:

1. Data privacy protects personal information from unauthorised access and use.
2. GDPR: EU regulation with 6 principles and 8 data subject rights.
3. CCPA: California law with rights to know, delete, and opt-out.
4. Blockchain challenges: immutability, pseudonymity, data minimisation, cross-border data transfers.
5. Privacy-enhancing technologies: ZKPs, differential privacy, SMPC.
6. Strategies: off-chain storage, encryption, zero-knowledge proofs, privacy by design.

Privacy Compliance for Blockchain:
  - Store personal data off-chain (in encrypted databases).
  - Store only hashes on-chain (for verification).
  - Use zero-knowledge proofs for verification without data exposure.
  - Implement consent management.
  - Provide data deletion mechanisms (data subject rights).
  - Design for privacy from the start (Privacy by Design).
  - Conduct regular privacy impact assessments.
""")