FieldShield Features and Benefits

 

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Features / Benefits

IRI FieldShield helps you adhere to 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 clear as you secure the others with one or more supplied or custom data masking functions.

Consider some of the advantages of using FieldShield:

Sensitive data discovery and classification


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

Field-level protection


Protect faster and surer than other, bulk protection methods. Leave non-sensitive data in their original formats, and available for regular processing. Even if one field is compromised, the others stay safe with their own protection (vs. breaches where one password exposes all).

Rich functional choices


More than a dozen categories of static data masking functions -- including format-preserving encryption, redaction, and pseudonymization -- allow you to make security decisions on the nature of each datum and considerations like: security level, reversibility, ciphertext appearance, and speed. FieldShield also has several options for dynamic data masking.

Cross-platform executable and libraries


Deploy concealment and revelation widely and easily, through bulk/batch, real-time applications, or through stored (SQL) procedures (e.g., in-situ encryption).

Database- and file-agnostic


Secure data at source and endpoints across multiple DB platforms and file formats with the same product and metadata, and/or at the same time.

Random value lookups


Pseudonymize PII using data from the same, other-table, or third-party source file(s) to provide realism, safety, and the option of reversibility.

Cross-table masking rules


Define, enforce, and re-use protections for common-named tables and the data class libraries you identified across the database(s). Preserve referential integrity because common start values get the same end values.

National ID (NID) masking


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

Hashing and tokenization


Validate the integrity and improve the security of encryption operations.

XML audit log file


Verify privacy law compliance efforts and support query and reporting of all runtime details.

Re-ID risk scoring


Graphical and detailed reports from peer-reviewed quasi-identifier statistical analysis help data governance teams comply with the HIPAA Expert Determination Method rule and FERPA requirements for low-likelihood re-identification.

Blurring and generalization


Anonymize quasi-identifiers to reduce re-identification risk while retaining the data's research or marketing value.

Multi-source, multi-target


Save protection design and execution time by protecting many different files and tables in the same job script and I/O pass. Consolidate multiple protections and authorizations in a single target, and thus reduce both throughput and data synchronization concerns; i.e., different people can reveal different fields from the same document. 

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

Metadata interoperability


FieldShield shares the data and job definition 4GL โ€‹of its parent CoSort SortCL programs so you can combine data masking with data transformation, migration, and reporting functions in the same job script and I/O pass if you have a CoSort package or Voracity platform license. Its masking functions are also part of compatible scripts involved in DB subsetting, data cleansing, ETL, and test data synthesis.

You can also run and manage the open, self-documenting job scripts of FieldShield outside IRI Workbench, and seamlessly team-share those jobs through 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 data used in those apps. And, you can run FieldShield job scripts alongside Actifio or Commvault database cloning operations to mask those copies.

User-friendly job design options


Six different ways to create masking jobs in the same Eclipse front-end allows users to work in the style they prefer while reducing their learning curve in discovering and protecting data in disparate 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 encryption.

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