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Security & Compliance

Overview​

Organizations face increasing regulatory requirements around data privacy, security, and auditability. PII exposure, data breaches, and compliance violations often occur during data collection and transmission - before security controls are applied. Processing data at the edge enables enforcement of security policies and compliance rules at the source, preventing violations before sensitive data enters your infrastructure.

Expanso's Approach to Security & Compliance​

Expanso Edge applies security policies and compliance rules at the point of data collection, before transmission or storage. Edge agents automatically detect, redact, and control sensitive data according to configurable policies managed centrally.

Key capabilities:

  • Automated PII Detection: Identify and redact credit cards, SSNs, email addresses, phone numbers, and other PII using regex patterns or ML-based detection.
  • Policy Enforcement at Source: Apply data minimization, anonymization, and encryption policies before data leaves edge locations.
  • Audit Trail Generation: Automatically create tamper-evident audit logs showing what data was collected, transformed, and transmitted - required for GDPR, HIPAA, and SOC 2 compliance.
  • Encryption in Motion: Apply field-level encryption or format-preserving encryption at the edge, ensuring sensitive data is protected throughout its lifecycle.
  • Consent Management: Filter and route data based on user consent preferences, ensuring only authorized data flows to specific destinations.

Benefits of Edge Security & Compliance​

Risk Reduction

  • Eliminate PII from datasets before transmission, reducing breach exposure surface
  • Prevent accidental logging or storage of sensitive credentials and tokens
  • Apply defense-in-depth by enforcing policies at collection, not just at storage
  • Reduce blast radius of security incidents through source-level data minimization

Compliance Automation

  • Meet GDPR "privacy by design" requirements through automated edge redaction
  • Ensure HIPAA compliance by de-identifying PHI before transmission
  • Satisfy PCI-DSS requirements by preventing credit card data from entering logs or analytics
  • Generate audit trails required for SOC 2, ISO 27001, and other certifications

Operational Efficiency

  • Centrally manage compliance policies deployed to thousands of edge locations
  • Automatic application of new regulations without code changes
  • Reduce manual audit workload through automated compliance logging
  • Simplify data retention policies by collecting only necessary, compliant data

Common Patterns​

Automated PII Redaction Scan all data for patterns matching credit cards, SSNs, email addresses, phone numbers, and custom sensitive patterns. Replace detected values with tokens or redacted placeholders before data leaves the edge.

Field-Level Encryption Encrypt specific fields containing sensitive data at the edge using customer-managed keys. Only authorized downstream systems with decryption keys can access the original values.

Consent-Based Routing Check user consent preferences and route data accordingly: analytics-approved data to business intelligence, essential-only data to operational systems, full opt-out data is filtered entirely.

Audit Log Enrichment Automatically append compliance metadata to all events: who collected the data, when, under what policy, what transformations were applied, and where it was sent.

Data Minimization Apply principle of least privilege to data collection: filter unnecessary fields, aggregate granular data, and retain only what's required for legitimate business purposes.

Example Use Cases​

  • Healthcare providers de-identifying patient records at the source, maintaining HIPAA compliance while enabling clinical analytics and research
  • Retail companies redacting payment card data from logs and analytics streams, preventing PCI-DSS scope expansion while maintaining fraud detection capability
  • SaaS platforms enforcing user privacy preferences at the edge, routing data according to consent levels before it enters analytics pipelines
  • Financial institutions detecting and tokenizing account numbers, SSNs, and sensitive customer data in real-time logs before centralized storage

Next Steps​