Encryption
Protect data at rest and in transit with advanced encryption algorithms and key management systems. Encryption is the most mature control available and the one most often undermined by its key management rather than its cipher.
- AES-256 encryption for data at rest
- End-to-end encryption where the threat model includes the platform itself
- Key rotation policies, enforced rather than documented
- Hardware security modules for key custody
Data anonymization
Remove or modify personally identifiable information to protect individual privacy. The critical judgement is whether the result is genuinely anonymous — which takes it outside the scope of most regimes — or merely pseudonymous, which does not.
- Data masking techniques for non-production environments
- K-anonymity algorithms and the l-diversity and t-closeness refinements
- Differential privacy for aggregate release
- Synthetic data generation for development and testing
Access control
Implement robust authentication and authorization mechanisms to control data access. Most incidents are access failures rather than cryptographic ones.
- Multi-factor authentication
- Role-based access control, reviewed against actual usage
- Zero-trust architecture
- Privileged access management with session recording
Data privacy analytics
Monitor and analyze data privacy metrics to ensure compliance and identify potential risks before they become findings.
- Data privacy impact scoring
- Data flow monitoring
- Risk assessment tools
- Compliance dashboards that report exceptions rather than totals
Consent management
Manage user consent preferences and ensure compliance with consent requirements. Consent is only a lawful basis if it is genuinely free, specific, informed and withdrawable — and if you can prove all four.
- Consent collection platforms
- Preference management across channels
- Consent withdrawal tools that propagate downstream
- Audit trail systems recording what was shown and when
Data discovery
Automatically identify and classify sensitive data across your organization. Discovery is what keeps the inventory honest between manual reviews.
- Automated data scanning across structured and unstructured stores
- Pattern recognition for identifiers and sensitive categories
- Data classification tied to handling rules
- Sensitive data mapping feeding the ROPA