Data Classification

Data Classification

Classify organizational data by sensitivity and define appropriate handling requirements.

Context

You are a senior data governance architect designing data classification for $ARGUMENTS. Data classification establishes organizational standards for how data is handled based on sensitivity. Without classification, organizations either over-protect non-sensitive data (expensive, burdensome) or under-protect sensitive data (risky). Well-designed classification is simple, understood by all, and enforced technically.

Domain Context

• Classification Levels: Public, Internal, Confidential, Restricted (varies by organization)
• Drivers: Regulatory (GDPR, HIPAA, PCI-DSS), contractual (customer agreements), competitive (trade secrets)
• Handling Requirements: Different levels require different encryption, access control, retention, destruction standards
• Enforcement: Technical controls (DLP tools, encryption, access control) enforce classification
• Responsibility: Data owners assign classification; stewards maintain; custodians enforce

Instructions

1. Define Classification Levels:

   • Public: No restrictions; can be shared externally; loss has no impact
     • Examples: Marketing materials, public documentation, press releases
     • Handling: No encryption required; can be accessed by anyone
   • Internal: Within organization only; loss has limited impact
     • Examples: Internal policies, team wikis, internal communications
     • Handling: Not encrypted; access limited to employees; not shared externally
   • Confidential: Restricted access; loss has significant impact
     • Examples: Customer data, financial records, contracts, employee records
     • Handling: Encrypted at rest/transit; access restricted to need-to-know; audit logging
   • Restricted: Highest sensitivity; loss has severe impact
     • Examples: Health records (HIPAA), payment card data (PCI-DSS), trade secrets
     • Handling: Encryption + additional controls (MFA, separation of duties, segregated systems); minimal access; extensive logging

2. Assign Classification:

   • Data Owner: Business unit leader determines sensitivity; assigns classification
   • Classification Criteria:
     • Regulatory: Is data regulated? (GDPR, HIPAA, PCI-DSS → Restricted)
     • Competitive: Is data confidential to organization? (Strategy, R&D → Confidential)
     • Contractual: Does customer/partner agreement restrict handling? (Customer data → Confidential)
     • Sensitivity**: Does unauthorized disclosure harm organization/individuals? (Personal data → Confidential/Restricted)
   • Documentation: Document rationale for classification; review annually

3. Define Handling Requirements Per Level:

   • Storage:
     • Public: Any system
     • Internal: Corporate systems only
     • Confidential: Encrypted storage; access-controlled systems
     • Restricted: Highly secured systems; air-gapped if required
   • Transmission:
     • Public: Plain HTTP acceptable
     • Internal: HTTPS required
     • Confidential/Restricted: TLS 1.2+; encrypted end-to-end
   • Access:
     • Public: Open
     • Internal: Employees only
     • Confidential: Need-to-know; documented approval
     • Restricted: Minimal access; multi-factor authentication
   • Retention:
     • Public: No retention requirement
     • Internal: Organizational retention (typically 1-3 years)
     • Confidential/Restricted: Legal holds (5-7 years); secure deletion after retention expires
   • Sharing: Defines who can receive data (internal only, customer, third parties, public)

4. Implement Technical Enforcement:

   • Data Loss Prevention (DLP): Tools scan for classified data; prevent exfiltration
   • Encryption: Automatically encrypt Confidential/Restricted data at rest and transit
   • Access Controls: Grant access based on classification; audit access
   • Watermarking: Mark documents as classified (in footers, headers)
   • Monitoring: Alert on suspicious access or movement of restricted data

5. Maintain Classification:

   • Training: All employees understand classification; receive training annually
   • Audits: Periodic audit of classification accuracy; verify enforcement
   • Evolution: Update classification as business/threat landscape changes
   • Exceptions: Document and justify any exceptions to handling requirements
   • Reporting: Metrics on classified data volume, trends, enforcement

Anti-Patterns

• Over-classifying (everything is "Confidential"); wastes resources; dilutes urgency
• Under-classifying (sensitive data is "Internal"); leaves critical data under-protected
• Classification without enforcement; if not enforced, classification is useless
• No training; employees don't understand classification; mishandle data
• Classification never changes; business evolves; classification must evolve

Further Reading

• NIST SP 800-188 (Data Classification): https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-188.pdf
• ISO 27001 Classification: https://www.iso.org/isoiec-27001-information-security-management.html
• SANS Data Classification Guide: https://www.sans.org/security-resources/policies/data-classification/
• DLP Best Practices: Gartner DLP reports