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Platform service: Protection

Data protection designed for data consumption.

Resolve the eternal struggle between data security and data utility. Precisely apply field-level data protection—tokenization, encryption, masking and more—based on specific security and utility needs.
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DATA-CENTRIC DATA PROTECTION

Balance security needs with data utility.

Protegrity provides the most complete range of data protection methods, enabling organizations to develop fit-for-purpose data protection strategies that meet their most pressing data security challenges.

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Field-Level Protection In The Cloud

Tokenize or mask sensitive customer data (PII, PCI, etc.) stored in platforms like Snowflake, BigQuery, or Redshift, while preserving usability for reporting, AI, and analytics.

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De-Identification

Anonymize or pseudonymize sensitive datasets (like patient or customer data) to enable secure and compliant research, analytics, and ML model development.

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Role-Based Masking

Dynamically mask or redact sensitive fields (e.g., payment info, account numbers) based on user role or session context within internal applications or BI tools.

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Synthetic Data

Generate statistically realistic but artificial datasets for testing applications or training AI/ML pipelines when real production data cannot be used due to privacy or legal restrictions.

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Cross-Border Data Tokenization

Apply region-specific tokenization or other protection methods to meet data localization requirements like GDPR while enabling consistent global operations and reporting.

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Proxy-Based Protection for Legacy Systems

Secure sensitive data flowing to or from legacy applications and systems using proxy-based protectors (like DSG) without requiring complex or risky modifications to the original application code.

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Accelerate data access and turn data security into a competitive advantage with Protegrity’s uniquely data-centric approach to data protection.

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CORE PROTECTION METHODS

Protection Methods for diverse data environments.

Apply tokenization, masking, encryption, or anonymization at the field level using Protectors—enforced through a central policy engine. Maintain data usability while aligning protection to your systems, roles, and regulatory needs.
01
Tokenization
Replace sensitive data elements with non-sensitive (and often format-preserving) token values using Protegrity’s scalable approach to vaultless tokenization—maintaining usability in downstream systems and analytics.
02
Encryption
Apply standards-based symmetric encryption (AES) to sensitive data fields that require reversible protection—commonly used in regulated environments with strict data controls.
03
Masking
Obscure part or all of a data element based on policy rules. Use static masking for permanent changes (e.g., test data creation) or dynamic masking based on user or session context at runtime.
04
Hashing
Apply one-way cryptographic functions to data for integrity verification or secure lookups and indexing—where original values don’t need to be revealed but matching is required.
05
Anonymization
Irreversibly alter data by removing or transforming direct and indirect identifiers to prevent individual identification—suitable for secondary analysis, research, and secure data sharing.
06
Pseudonymization
Substitute identifying fields with persistent but non-identifiable tokens, maintaining linkage for longitudinal analysis while minimizing re-identification risk compared to using raw data.
07
Synthetic Data
Generate statistically similar but artificial datasets based on original data characteristics—ideal for testing, development, training AI/ML models, or demos when real data access is restricted.
    ENFORCEMENT POINTS

    APPLY PROTECTION ANYWHERE IN YOUR ARCHITECTURE

    Protegrity’s field-level, format-preserving protection methods can be applied consistently via various mechanisms—Protegrity Protectors—embedded across your data environment. Select the enforcement point(s) that best fits your architecture and specific use case needs.
    EXPLORE ALL PROTEGRITY PROTECTORS
    Native
    Protectors
    Embedded enforcement directly within data platforms (databases, cloud DWH, file systems).
    Proxy-
    based
    Intercept data in transit via gateways or proxies (like DSG for JDBC) without app changes.
    Connectors/
    SDKs
    Embed protection logic directly into custom or third-party applications via APIs/SDKs.
    Batch
    Utilities
    Apply protection transformations offline to files or database tables via scheduled jobs or scripts.

    THE LATEST
    FROM PROTEGRITY

    Explore Our Resource Library
    EBooks

    Re-Thinking the Path to the Cloud: A Guide for Healthcare Providers

    1 min read • Nov 18, 2024
    Case Studies

    Flexible Data Protection Enables Insurer to Scale Data Analytics in the Cloud

    1 min read • Nov 13, 2024
    EBooks

    Digital Transformation Starts with You

    0 min read • Apr 19, 2023
    PLATFORM SERVICES

    ENTERPRISE DATA SECURITY
    IN A SINGLE PLATFORM

    Explore the additional core services of the Protegrity Data Security Platform.

    Discovery

    Identify sensitive data (PII, PHI, PCI, IP) across structured and unstructured sources using ML and rule-based classification.

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    Governance

    Define and manage access and protection policies based on role, region, or data type—centrally enforced and audited across systems.

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    Protection

    Apply field-level protection methods—like tokenization, encryption, or masking—through enforcement points such as native integrations, proxies, or SDKs.

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    Privacy

    Support analytics and AI by removing or transforming identifiers using anonymization, pseudonymization, or synthetic data generation—balancing privacy with utility.

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    See the protegrity platform in action

    Accelerate data access and turn data security into a competitive advantage with Protegrity’s uniquely data-centric approach to data protection.

    Get an online or custom live demo.

    TRY FOR FREEBOOK A DEMO