FieldShield's Features & Benefits

Some of the special features included and why you should be interested

FieldShield
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Functions / Advantages

IRI FieldShield helps you comply with both business rules and data privacy laws in a data-centric context.

 Profile and protect database tables, flat files, and other sources at the column (field) level. Choose which columns remain unmasked while masking others with one or more supplied or custom data masking functions.

Consider some of the benefits of using FieldShield:

Sensitive Data Detection and Classification

Centrally define and globally locate PII, PHI, and other data matching patterns, lookup, and fuzzy search criteria in relational databases, flat files, and semi-/unstructured sources. Text and dashboard reports of profiling and search results can be used for audit and SIEM environments, as well as automatically during masking operations.

Protect faster and more securely than other mass protection methods. Leave sensitive data in its original format and make it available for regular processing. Even if one field is compromised, the others remain secure with their own protection (vs. breaches where one password exposes everything).

More than a dozen categories of static data masking functions—including format-preserving encryption, redaction, fabrication, and pseudonymization—enable you to make security decisions based on the nature of individual data and considerations such as security level, reversibility, ciphertext appearance, and speed. FieldShield also features several options for dynamic data masking.

Provide disguises and revelations broadly and simply, through bulk/batch, real-time applications, or through stored (SQL) procedures (e.g., in-situ encryption).

Secure data at sources and endpoints across multiple DB platforms and file formats using the same product, the same metadata, and the same masking capabilities simultaneously.

Random Value Lookups.

Pseudonymize PII using data from the same table, another table, or a third-party source file to ensure realism, security, and the possibility of reversibility.

Define, enforce, and reuse protection measures for commonly named tables and the data class libraries you have identified in the databases. Preserve referential integrity with deterministic data masking functions, as common initial values result in the same final values.

Save research and development time in complying with de-identification requirements and local data privacy laws with standard and custom masks.

Validation of the integrity and improvement of the security of encryption processes.

Check compliance with data protection regulations and support the querying and reporting of all runtime details.

Re-ID Risk Scoring

Graphical and detailed reports from peer-reviewed statistical quasi-identifier analyses assist data governance teams with HIPAA expert determination method compliance and FERPA low-probability re-identification requirements.

Anonymization of quasi-identifiers to reduce the risk of re-identification while preserving the research or marketing value of the data.

Save time in protection design and execution by protecting many different files and tables in a single job script and I/O pass. Consolidate multiple protections and entitlements into a single target thereby reducing both throughput and data synchronization concerns; i.e., different people can expose different fields of the same document.

FieldShield data classes and masking functions are also shared with IRI CellShield EE and IRI DarkShield for semi/unstructured data sources, respectively. This means that data categories and rules are defined once and apply globally across the entire product line, and data that has been obfuscated in one source with one tool can be restored in another source.

FieldShield leverages the data and job definition 4GL of its parent CoSort SortCL programs, allowing you to combine data masking with data transformation, migration, and reporting capabilities in the same job script and I/O pass when you have a CoSort package or Voracity platform license. The masking functions are also part of compatible scripts involved in DB sub-setting, data cleansing, ETL, and test data synthesis.

 

You can also execute and manage FieldShield's open, self-documenting job scripts outside of IRI Workbench and seamlessly collaborate on these jobs in a team using any source code control system compatible with Eclipse™ (e.g., Git). AnalytiXDS (now Erwin) Mapping Manager and MIMB users can convert existing metadata in BI, CRM, DB, ETL, and modeling tools into the Data Definition File (DDF) format that FieldShield uses to mask the data used in those applications. You can also execute FieldShield job scripts alongside Windocks, Actifio, or Commvault database cloning operations to mask these copies.

Six different ways to create masking jobs in the same Eclipse front-end allow users to work in their desired style while shortening their learning curve for finding and protecting data from different sources. Data layouts and field functions are self-documenting, so data architects, DBAs, and compliance teams can easily design, modify, and verify jobs. The free Eclipse™ UI (IRI Workbench) eliminates the complexity and cost of proprietary design studios and DB-vendor-specific column redaction.