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Data-Centric Security

FieldShield: Data Masking

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IRI Data Masking Software in 2018 Market Guide

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Profile and Protect Data at Risk

Nullify data breaches by masking PII in your DBs and files. Automatically find and classify it, then encrypt, pseudonymize, redact, and more while preserving its referential integrity.

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Comply with Data Privacy Laws

FieldShield de-identifies data subject to CIPSEA, DPA, FERPA, GDPR, GLBA, HIPAA, PCI, POPI, etc. It also helps you verify compliance via XML audit logs and re-identification risk scores.

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Protect Data throughout its Lifecycle

Secure your data at every stage by applying FieldShield functions in IRI Voracity operations. Anonymize during data integration (ETL), federation, replication, testing, and analytics.

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FieldShield Use Cases

Payment Card Industry Data (PCI)

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"FieldShield decrypts and re-encrypts fields in our credit card migration and test sources, and easily generates and manages encryption keys."

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Protected Health Information (PHI)

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"We continue to rely on FieldShield for flat-file and DB de-identification in order to comply with government healthcare privacy regulations"

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Personally Identifiable Information (PII)

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"We use FieldShield to anonymize HR data in complex file feeds, and to segment and substitute values based on field-level conditions."

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Do You Need FieldShield? Find Out

Complete Data Masking

Every Source

  • Flat Files
  • RDB & NoSQL DBs
  • Semi-structured Files
  • Mainframe / Index Files
  • S3, HDFS, MQTT, Kafka
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Every Protection

  • Encryption & Decryption
  • Blurring & Scrambling
  • Encoding & Decoding
  • Pseudonymization
  • Character Masking
  • Randomization
  • Hashing
  • Expressions
  • String Manipulations
  • Tokenization
  • Row/Column Removal
  • Custom Functions
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Every Deployment

  • Command Line
  • Eclipse GUI
  • Batch/Shell Scripts
  • System/API Library Calls
  • In Situ/SQL Procedures
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Learn More About FieldShield

Data Masking White Paper Download Now

What Others Are Reading

Data Masking vs. Data Encryption

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Do you know the differences between them? Learn about these two popular forms of data obfuscation and when to use them.

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Which Masking Function is Best?

Venetian Masks

Read this review of the important decision criteria, including realism, reversibility, consistency, speed, and security. 

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PCI Tokenization in FieldShield

Credit Cards

The Payment Card Industry Data Security Standard, or PCI DSS, requires encryption or tokenization of primary account numbers.

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Take the FieldShield Quiz

  • Do you collect or process PII or other "data at risk"? Do you know where (all of) it is?
  • Is that data safe from a breach; i.e., could it be used were it stolen or exposed?
  • Does your department comply with data privacy regulations? Can you prove it?
  • Do you use multiple tools or methods to protect different DB columns in different ways?
  • Can you protect only the data at risk, so you can see and use the non-sensitive data?
  • Does your masked data look real enough? Is it referentially correct?
  • Can you score your masked data sets for re-ID risk and anonymize quasi-identifers?
  • Does it take too long to learn, implement, modify, or optimize your data masking jobs?
  • Can you mask data in your ETL, subsetting, migration/replication, CDC or reporting tasks?
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