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11. Data Classification, Security, Encryption, Backups & Restoration
The Digital Operational Resilience Act (DORA) places a significant emphasis on the protection and resilience of data, requiring financial entities to implement robust processes for data classification, security, encryption, backups, and restoration. These measures aim to protect sensitive and critical data, ensure its integrity, and enable swift recovery in the event of incidents or disruptions.

by Sylvan Ravinet

The StratOps way to accelerate DORA
This guide on Data Classification, Security, Encryption, Backups & Restoration can help you achieve DORA compliance. Faster. Part of my 12-capabilities cyber framework.
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1. Regulatory Foundation
1.1 Introduction
This guide provides a comprehensive framework for meeting DORA's data security requirements. It covers classification, protection controls, lifecycle management, and integration with other capabilities.
1.1 Regulatory Foundation
DORA Regulation 2022/2554, Article 9: Information security requirements
RTS 2024/1774, Articles 11-12: Data and system security requirements
RTS 2024/1774, Article 6: Encryption and cryptographic controls
Additional regulatory guidance from European Supervisory Authorities (ESAs)
2. Regulatory Requirements
2.1 Data Classification
[RTS 2024/1774 Art. 11]
Financial entities must:
  • Establish and document a data classification methodology
  • Define and implement protection requirements for each classification level
  • Maintain clear ownership and accountability for data assets
  • Regularly review and update the classification scheme
  • Consider data classification when performing ICT asset classification (per Article 8)
2.2 Security Controls
[RTS 2024/1774 Art. 11-12]
Financial entities must implement:
  • Access control mechanisms appropriate to data sensitivity
  • Logging and monitoring capabilities
  • Data protection measures proportionate to classification
  • Regular review and validation of controls
2.3 Encryption Requirements
[RTS 2024/1774 Art. 6]
Financial entities must:
  • Establish and implement an encryption policy
  • Define cryptographic controls for data protection
  • Implement key management procedures
  • Regularly review encryption effectiveness
Financial entities must implement protection for data in all states:
  • Data at rest: Implement encryption for stored data
  • Data in transit: Ensure secure transmission with appropriate protocols
  • Data in use: Protect data during processing
  • Key management: Secure generation, storage, and rotation of cryptographic keys
2.4 Data Protection States
[RTS 2024/1774 Art. 11]
Financial entities must implement appropriate controls for data in all states:
  • Data at rest:
  • Secure storage mechanisms
  • Access controls
  • Encryption where appropriate to risk
  • Data in transit:
  • Secure transmission protocols
  • Network security controls
  • Encryption during transmission
  • Data in use:
  • Memory protection
  • Process isolation
  • Access monitoring
3. Implementation Guidance
The following sections provide examples and suggested practices for implementing the above requirements. These should be adapted based on your organization's specific context, risk assessment, and classification scheme.
3.1 Classification Framework Examples
Example Classification Approach
Note: These are illustrative examples only. Your organization must define its own scheme based on:
  • Risk assessment outcomes
  • Business requirements
  • Regulatory obligations
  • Relationship with ICT asset classification (per Article 8 of DORA)
  • Data classification is a key input for ICT asset classification
  • ICT assets inherit criticality from the data they process/store
  • Changes in data classification may require updates to ICT asset classification
The classification methodology should be:
  • Documented as part of the information security policy
  • Supported by clear control requirements for each level
  • Regularly reviewed and updated
  • Aligned with the entity's risk appetite and regulatory obligations
3.2 Security Control Examples
The following are example controls demonstrating the principle of proportionate security measures:
3.3 Example Cryptographic Approaches
Common industry practices include:
  • AES-256 for data at rest
  • TLS 1.2+ for data in transit
  • Hardware Security Modules (HSMs) for key management
  • Regular key rotation schedules
4. Data Lifecycle Management
4.1 Regulatory Requirements
Financial entities must implement controls for:
  • Data collection and processing in compliance with regulations
  • Secure storage and retention
  • Appropriate access controls
  • Secure disposal methods
4.2 Implementation Examples
The following are suggested approaches:
  • Data collection and processing in compliance with regulations
  • Secure storage and retention
  • Appropriate access controls
  • Secure disposal methods
5. Integration Points
5.1 Incident Management
  • Data breach detection capabilities
  • Impact assessment procedures
  • Response playbooks
  • Recovery procedures
5.2 Resilience Testing
  • Data security control validation
  • Recovery procedure testing
  • Classification effectiveness assessment
  • Control automation testing
5.3 Threat Management
  • Data-focused threat monitoring
  • Vulnerability assessment
  • Risk mitigation strategies
  • Threat intelligence integration
5.4 Crisis Communication
  • Data breach notification procedures
  • Stakeholder communication plans
  • Regulatory reporting requirements
  • Public relations management
6. Common Challenges and Solutions
6.1 Data Discovery
Challenge: Maintaining complete data inventory Solutions:
  • Automated discovery tools
  • Regular manual reviews
  • Classification automation
  • Integration with asset management
6.2 Protection Implementation
Challenge: Consistent control application Solutions:
  • Risk-based implementation
  • Control automation
  • Regular validation
  • Continuous monitoring
6.3 Legacy Systems
Challenge: Limited security capabilities Solutions:
  • Compensating controls
  • System isolation
  • Modernization planning
  • Enhanced monitoring
7. Key Success Factors
Success in DORA data security compliance requires:
Complete and current data inventory
Clear, risk-based classification scheme
Appropriate and automated controls
Regular testing and validation
Comprehensive documentation
Integration with other DORA capabilities
Strong governance and oversight
Regular training and awareness
Links to Related DORA Compliance Themes
For a comprehensive understanding of DORA compliance, this guide aligns with the following related topics:
For detailed implementation guidance, refer to DORA's RTS and ITS documentation and related guides within this compliance series.
The StratOps way to accelerate DORA
CISO & Advisor | My StratOps newsletter helps cybersecurity experts achieve more, faster.

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