# Privacy Policies and GDPR Compliance

## Overview

This document establishes comprehensive privacy policies and procedures to ensure compliance with data protection regulations including GDPR, CCPA, and other applicable privacy laws. These policies protect individual privacy rights while enabling legitimate business operations.

## Privacy Policy Framework

### Core Privacy Principles

**1. Lawfulness, Fairness, and Transparency**
- Personal data processed lawfully, fairly, and transparently
- Clear communication about data processing purposes
- Transparent privacy notices and consent mechanisms

**2. Purpose Limitation**
- Data collected for specified, explicit, and legitimate purposes
- No further processing incompatible with original purposes
- Regular review of processing purposes

**3. Data Minimization**
- Data adequate, relevant, and limited to necessary purposes
- Regular assessment of data collection requirements
- Automated data reduction where possible

**4. Accuracy**
- Personal data accurate and kept up to date
- Reasonable steps to ensure accuracy
- Prompt correction or deletion of inaccurate data

**5. Storage Limitation**
- Data kept only as long as necessary for purposes
- Clear retention periods and deletion schedules
- Regular review and purging of outdated data

**6. Integrity and Confidentiality**
- Appropriate security measures for personal data
- Protection against unauthorized processing
- Regular security assessments and updates

### Privacy by Design Implementation

**Technical Measures:**
```yaml
privacy_by_design:
  data_minimization:
    - collect_only_necessary_data: true
    - automated_data_reduction: true
    - purpose_based_collection: true
  
  consent_management:
    - granular_consent_options: true
    - easy_consent_withdrawal: true
    - consent_audit_trail: true
  
  data_protection:
    - encryption_at_rest: "AES-256"
    - encryption_in_transit: "TLS 1.3"
    - pseudonymization: true
    - anonymization: true
  
  access_controls:
    - role_based_access: true
    - principle_of_least_privilege: true
    - regular_access_reviews: true
```

## GDPR Compliance Framework

### Data Subject Rights Implementation

**Right to Information (Articles 13-14):**
```python
# Privacy notice generator
class PrivacyNoticeGenerator:
    def __init__(self):
        self.required_information = [
            'controller_identity',
            'processing_purposes',
            'legal_basis',
            'legitimate_interests',
            'data_categories',
            'recipients',
            'retention_periods',
            'data_subject_rights',
            'withdrawal_consent',
            'complaint_rights',
            'automated_decision_making'
        ]
    
    def generate_privacy_notice(self, processing_context):
        """Generate GDPR-compliant privacy notice"""
        
        notice = {
            'controller': {
                'name': processing_context['controller_name'],
                'contact': processing_context['controller_contact'],
                'dpo_contact': processing_context['dpo_contact']
            },
            'processing_purposes': processing_context['purposes'],
            'legal_basis': processing_context['legal_basis'],
            'data_categories': processing_context['data_types'],
            'retention': processing_context['retention_periods'],
            'rights': self.get_data_subject_rights(),
            'last_updated': datetime.now().isoformat()
        }
        
        return notice
    
    def get_data_subject_rights(self):
        """Standard data subject rights information"""
        
        return {
            'access': 'Right to obtain confirmation and copy of personal data',
            'rectification': 'Right to correct inaccurate personal data',
            'erasure': 'Right to deletion of personal data',
            'restriction': 'Right to restrict processing',
            'portability': 'Right to receive data in structured format',
            'objection': 'Right to object to processing',
            'automated_decisions': 'Right not to be subject to automated decision-making'
        }
```

**Data Subject Request Management:**
```python
# GDPR request handling system
from enum import Enum
from datetime import datetime, timedelta

class RequestType(Enum):
    ACCESS = "access"
    RECTIFICATION = "rectification"
    ERASURE = "erasure"
    RESTRICTION = "restriction"
    PORTABILITY = "portability"
    OBJECTION = "objection"

class DataSubjectRequestManager:
    def __init__(self, db_connection):
        self.db = db_connection
        self.response_deadline = timedelta(days=30)
        self.complex_request_extension = timedelta(days=60)
    
    def submit_request(self, request_data):
        """Submit new data subject request"""
        
        request_id = self.generate_request_id()
        
        request_record = {
            'request_id': request_id,
            'request_type': request_data['type'],
            'data_subject_id': request_data['subject_id'],
            'request_details': request_data['details'],
            'submission_date': datetime.now(),
            'deadline': self.calculate_deadline(request_data['type']),
            'status': 'submitted',
            'assigned_to': self.assign_request_handler(request_data['type'])
        }
        
        self.save_request(request_record)
        self.send_acknowledgment(request_record)
        
        return request_id
    
    def process_access_request(self, request_id):
        """Process right of access request"""
        
        request = self.get_request(request_id)
        subject_id = request['data_subject_id']
        
        # Collect all personal data
        personal_data = self.collect_personal_data(subject_id)
        
        # Generate data export
        export_package = {
            'subject_id': subject_id,
            'export_date': datetime.now().isoformat(),
            'data_sources': personal_data,
            'processing_purposes': self.get_processing_purposes(subject_id),
            'retention_periods': self.get_retention_info(subject_id),
            'third_party_sharing': self.get_sharing_info(subject_id)
        }
        
        # Update request status
        self.update_request_status(request_id, 'completed', export_package)
        
        return export_package
    
    def process_erasure_request(self, request_id):
        """Process right to erasure request"""
        
        request = self.get_request(request_id)
        subject_id = request['data_subject_id']
        
        # Check erasure conditions
        erasure_assessment = self.assess_erasure_request(subject_id)
        
        if erasure_assessment['can_erase']:
            # Perform erasure
            erasure_results = self.execute_erasure(subject_id, erasure_assessment['scope'])
            
            self.update_request_status(request_id, 'completed', erasure_results)
            return erasure_results
        else:
            # Provide reasons for refusal
            refusal_reasons = erasure_assessment['refusal_reasons']
            self.update_request_status(request_id, 'refused', refusal_reasons)
            return {'status': 'refused', 'reasons': refusal_reasons}
    
    def assess_erasure_request(self, subject_id):
        """Assess whether erasure request can be fulfilled"""
        
        assessment = {
            'can_erase': True,
            'refusal_reasons': [],
            'scope': 'full'
        }
        
        # Check legal obligations
        if self.has_legal_retention_obligation(subject_id):
            assessment['can_erase'] = False
            assessment['refusal_reasons'].append('Legal obligation to retain data')
        
        # Check legitimate interests
        if self.has_overriding_legitimate_interest(subject_id):
            assessment['can_erase'] = False
            assessment['refusal_reasons'].append('Overriding legitimate interests')
        
        # Check ongoing contracts
        if self.has_active_contract(subject_id):
            assessment['scope'] = 'partial'
            assessment['refusal_reasons'].append('Data necessary for contract performance')
        
        return assessment
```

### Consent Management

**Consent Collection and Management:**
```python
# Consent management system
class ConsentManager:
    def __init__(self, db_connection):
        self.db = db_connection
    
    def collect_consent(self, subject_id, consent_data):
        """Collect and record consent"""
        
        consent_record = {
            'subject_id': subject_id,
            'consent_id': self.generate_consent_id(),
            'purposes': consent_data['purposes'],
            'consent_method': consent_data['method'],  # opt-in, checkbox, etc.
            'consent_text': consent_data['consent_text'],
            'timestamp': datetime.now(),
            'ip_address': consent_data.get('ip_address'),
            'user_agent': consent_data.get('user_agent'),
            'status': 'active'
        }
        
        # Validate consent requirements
        if self.validate_consent(consent_record):
            self.save_consent(consent_record)
            return consent_record['consent_id']
        else:
            raise ValueError("Invalid consent - does not meet GDPR requirements")
    
    def validate_consent(self, consent_record):
        """Validate consent meets GDPR requirements"""
        
        # Check if consent is freely given
        if not self.is_freely_given(consent_record):
            return False
        
        # Check if consent is specific
        if not self.is_specific(consent_record):
            return False
        
        # Check if consent is informed
        if not self.is_informed(consent_record):
            return False
        
        # Check if consent is unambiguous
        if not self.is_unambiguous(consent_record):
            return False
        
        return True
    
    def withdraw_consent(self, subject_id, consent_id, withdrawal_reason=None):
        """Process consent withdrawal"""
        
        withdrawal_record = {
            'consent_id': consent_id,
            'subject_id': subject_id,
            'withdrawal_date': datetime.now(),
            'withdrawal_reason': withdrawal_reason,
            'withdrawal_method': 'user_request'
        }
        
        # Update consent status
        self.update_consent_status(consent_id, 'withdrawn')
        
        # Record withdrawal
        self.save_withdrawal(withdrawal_record)
        
        # Stop processing based on withdrawn consent
        self.stop_consent_based_processing(subject_id, consent_id)
        
        return withdrawal_record
    
    def get_consent_status(self, subject_id, purpose=None):
        """Get current consent status for subject"""
        
        query = """
        SELECT purpose, status, consent_date, withdrawal_date
        FROM consent_records 
        WHERE subject_id = %s
        """
        
        params = [subject_id]
        
        if purpose:
            query += " AND purpose = %s"
            params.append(purpose)
        
        consents = pd.read_sql(query, self.db, params=params)
        
        return consents.to_dict('records')
```

## Data Protection Impact Assessment (DPIA)

### DPIA Framework

**DPIA Trigger Criteria:**
```yaml
dpia_triggers:
  mandatory_dpia:
    - systematic_monitoring: "Large scale monitoring of publicly accessible areas"
    - sensitive_data_large_scale: "Large scale processing of special categories"
    - automated_decision_making: "Automated decisions with legal/significant effects"
  
  recommended_dpia:
    - new_technology: "Use of new technologies"
    - profiling: "Systematic profiling of individuals"
    - biometric_data: "Processing of biometric data"
    - genetic_data: "Processing of genetic data"
    - location_tracking: "Systematic location tracking"
    - children_data: "Processing of children's data"
```

**DPIA Process Implementation:**
```python
# Data Protection Impact Assessment system
class DPIAManager:
    def __init__(self):
        self.assessment_criteria = self.load_assessment_criteria()
    
    def initiate_dpia(self, processing_description):
        """Initiate DPIA for new processing activity"""
        
        dpia_id = self.generate_dpia_id()
        
        dpia_record = {
            'dpia_id': dpia_id,
            'processing_description': processing_description,
            'initiation_date': datetime.now(),
            'status': 'in_progress',
            'assessor': processing_description['data_controller'],
            'dpo_involved': True
        }
        
        # Conduct initial screening
        screening_result = self.conduct_screening(processing_description)
        
        if screening_result['dpia_required']:
            return self.conduct_full_dpia(dpia_record)
        else:
            dpia_record['status'] = 'not_required'
            dpia_record['screening_result'] = screening_result
            return dpia_record
    
    def conduct_full_dpia(self, dpia_record):
        """Conduct comprehensive DPIA"""
        
        assessment = {
            'necessity_assessment': self.assess_necessity(dpia_record),
            'proportionality_assessment': self.assess_proportionality(dpia_record),
            'risk_assessment': self.assess_privacy_risks(dpia_record),
            'mitigation_measures': self.identify_mitigation_measures(dpia_record),
            'residual_risk': self.calculate_residual_risk(dpia_record)
        }
        
        # Determine if consultation with supervisory authority needed
        if assessment['residual_risk']['level'] == 'high':
            assessment['supervisory_consultation'] = 'required'
        
        dpia_record['assessment'] = assessment
        dpia_record['completion_date'] = datetime.now()
        dpia_record['status'] = 'completed'
        
        return dpia_record
    
    def assess_privacy_risks(self, dpia_record):
        """Assess privacy risks for data subjects"""
        
        risks = []
        
        # Identify potential risks
        risk_categories = [
            'unlawful_processing',
            'discrimination',
            'identity_theft',
            'financial_loss',
            'reputational_damage',
            'loss_of_confidentiality',
            'unauthorized_reversal_pseudonymization'
        ]
        
        for category in risk_categories:
            risk_assessment = self.evaluate_risk_category(category, dpia_record)
            if risk_assessment['likelihood'] != 'negligible':
                risks.append(risk_assessment)
        
        return risks
```

## Cross-Border Data Transfers

### Transfer Mechanism Framework

**Adequacy Decisions and Safeguards:**
```yaml
transfer_mechanisms:
  adequacy_decisions:
    - countries: ["Andorra", "Argentina", "Canada", "Faroe Islands", "Guernsey", "Israel", "Isle of Man", "Japan", "Jersey", "New Zealand", "Switzerland", "United Kingdom", "Uruguay"]
    - requirements: "No additional safeguards required"
  
  standard_contractual_clauses:
    - version: "2021 SCCs"
    - modules: ["Controller to Controller", "Controller to Processor", "Processor to Processor", "Processor to Controller"]
    - requirements: "Transfer Impact Assessment required"
  
  binding_corporate_rules:
    - scope: "Intra-group transfers"
    - requirements: "Supervisory authority approval required"
  
  certification_mechanisms:
    - examples: ["Privacy Shield successor", "ISO 27001", "SOC 2"]
    - requirements: "Binding enforcement mechanisms required"
```

**Transfer Impact Assessment:**
```python
# Transfer Impact Assessment system
class TransferImpactAssessment:
    def __init__(self):
        self.adequacy_countries = self.load_adequacy_decisions()
        self.risk_factors = self.load_risk_factors()
    
    def assess_transfer(self, transfer_details):
        """Conduct Transfer Impact Assessment"""
        
        assessment = {
            'transfer_id': self.generate_transfer_id(),
            'destination_country': transfer_details['destination'],
            'data_categories': transfer_details['data_types'],
            'transfer_purpose': transfer_details['purpose'],
            'assessment_date': datetime.now()
        }
        
        # Check if adequacy decision exists
        if transfer_details['destination'] in self.adequacy_countries:
            assessment['adequacy_status'] = 'adequate'
            assessment['additional_safeguards'] = 'not_required'
            return assessment
        
        # Assess local laws and practices
        legal_assessment = self.assess_local_laws(transfer_details['destination'])
        
        # Evaluate safeguards effectiveness
        safeguards_assessment = self.assess_safeguards(transfer_details['safeguards'])
        
        # Determine if transfer can proceed
        assessment['legal_assessment'] = legal_assessment
        assessment['safeguards_assessment'] = safeguards_assessment
        assessment['transfer_decision'] = self.make_transfer_decision(
            legal_assessment, safeguards_assessment
        )
        
        return assessment
    
    def assess_local_laws(self, destination_country):
        """Assess local laws that may impact data protection"""
        
        # This would integrate with legal databases and expert analysis
        legal_factors = {
            'surveillance_laws': self.check_surveillance_laws(destination_country),
            'data_localization': self.check_localization_requirements(destination_country),
            'government_access': self.check_government_access_laws(destination_country),
            'judicial_redress': self.check_judicial_redress(destination_country)
        }
        
        risk_level = self.calculate_legal_risk(legal_factors)
        
        return {
            'destination': destination_country,
            'legal_factors': legal_factors,
            'risk_level': risk_level,
            'assessment_date': datetime.now()
        }
```

## Privacy Training and Awareness

### Privacy Training Program

**Training Requirements:**
```yaml
privacy_training:
  mandatory_training:
    - target_audience: "All employees"
    - frequency: "Annual"
    - topics: ["GDPR basics", "Data subject rights", "Incident reporting"]
    - duration: "2 hours"
  
  role_specific_training:
    data_processors:
      - topics: ["Data minimization", "Purpose limitation", "Security measures"]
      - frequency: "Bi-annual"
      - duration: "4 hours"
    
    developers:
      - topics: ["Privacy by design", "Data protection APIs", "Secure coding"]
      - frequency: "Quarterly"
      - duration: "3 hours"
    
    marketing_team:
      - topics: ["Consent management", "Direct marketing rules", "Profiling"]
      - frequency: "Quarterly"
      - duration: "2 hours"
```

### Privacy Incident Response

**Incident Classification and Response:**
```python
# Privacy incident response system
class PrivacyIncidentManager:
    def __init__(self):
        self.notification_deadlines = {
            'supervisory_authority': timedelta(hours=72),
            'data_subjects': 'without_undue_delay'
        }
    
    def report_incident(self, incident_details):
        """Report privacy incident"""
        
        incident_id = self.generate_incident_id()
        
        incident_record = {
            'incident_id': incident_id,
            'report_date': datetime.now(),
            'incident_type': incident_details['type'],
            'description': incident_details['description'],
            'affected_subjects': incident_details['affected_count'],
            'data_categories': incident_details['data_types'],
            'severity': self.assess_severity(incident_details),
            'status': 'reported'
        }
        
        # Immediate containment
        self.initiate_containment(incident_record)
        
        # Assess notification requirements
        notification_assessment = self.assess_notification_requirements(incident_record)
        
        if notification_assessment['authority_notification_required']:
            self.schedule_authority_notification(incident_record)
        
        if notification_assessment['subject_notification_required']:
            self.schedule_subject_notification(incident_record)
        
        return incident_record
    
    def assess_severity(self, incident_details):
        """Assess incident severity for notification requirements"""
        
        risk_factors = {
            'data_sensitivity': self.assess_data_sensitivity(incident_details['data_types']),
            'affected_count': incident_details['affected_count'],
            'likelihood_of_harm': self.assess_harm_likelihood(incident_details),
            'mitigation_measures': incident_details.get('existing_measures', [])
        }
        
        # Calculate risk score
        risk_score = self.calculate_risk_score(risk_factors)
        
        if risk_score >= 7:
            return 'high'
        elif risk_score >= 4:
            return 'medium'
        else:
            return 'low'
```

## Compliance Monitoring and Auditing

### Automated Compliance Monitoring

**Compliance Dashboard:**
```python
# Privacy compliance monitoring
class ComplianceMonitor:
    def __init__(self, db_connection):
        self.db = db_connection
        self.compliance_checks = self.load_compliance_checks()
    
    def run_daily_compliance_checks(self):
        """Run automated daily compliance checks"""
        
        results = {}
        
        # Check consent validity
        results['consent_compliance'] = self.check_consent_compliance()
        
        # Check data retention compliance
        results['retention_compliance'] = self.check_retention_compliance()
        
        # Check data subject request SLAs
        results['request_sla_compliance'] = self.check_request_sla_compliance()
        
        # Check data transfer compliance
        results['transfer_compliance'] = self.check_transfer_compliance()
        
        # Generate compliance report
        compliance_report = self.generate_compliance_report(results)
        
        # Alert on violations
        self.alert_on_violations(results)
        
        return compliance_report
    
    def check_consent_compliance(self):
        """Check consent management compliance"""
        
        # Check for expired consents
        expired_consents = self.find_expired_consents()
        
        # Check for processing without valid consent
        invalid_processing = self.find_processing_without_consent()
        
        # Check consent withdrawal processing
        unprocessed_withdrawals = self.find_unprocessed_withdrawals()
        
        return {
            'expired_consents': len(expired_consents),
            'invalid_processing': len(invalid_processing),
            'unprocessed_withdrawals': len(unprocessed_withdrawals),
            'compliance_score': self.calculate_consent_compliance_score()
        }
```
