Find and Fix Data at Risk
Classify PII centrally, find it globally, and mask it automatically. Preserve realism and referential integrity using encryption, pseudonymization, redaction, and other rules for production and test envrionments.Learn more
Comply with Data Privacy Laws
Delete, deliver, or anonymize data subject to CIPSEA, DPA, FERPA, GDPR, GLBA, HIPAA, PCI, POPI, etc. Verify compliance via human- and machine-readable search reports, job audit logs, and re-identification risk scores.Learn more
Protect Data throughout its Lifecycle
Optionally mask data as you map it. Apply FieldShield functions in IRI Voracity ETL, federation, migration, replication, subsetting, or analytic jobs. Or, run FieldShield from Actifio or Commvault jobs to mask DB clones. Retain consistency (determinstic masking) of values across sources.Learn more
FieldShield Use Cases
Payment Card Industry Data (PCI)
"FieldShield decrypts and re-encrypts fields in our credit card migration and test sources, and easily generates and manages encryption keys."Learn More
Protected Health Information (PHI)
"We continue to rely on FieldShield for flat-file and DB de-identification in order to comply with government healthcare privacy regulations"Learn More
Personally Identifiable Information (PII)
"We use FieldShield to anonymize HR data in complex file feeds, and to segment and substitute values based on field-level conditions."Learn More
Do You Need FieldShield? Find Out
Complete Data Masking
- Flat Files
- RDB & NoSQL DBs
- Semi-structured Files
- Mainframe / Index Files
- S3, HDFS, MQTT, Kafka
- Pipes, Procedures & URLs
- Excel Spreadsheets (CellShield)
- Unstructured Files & Faces (DarkShield)
- Blur or Bucket
- Bit Shift/Scramble
- Encrypt & Decrypt
- Encode & Decode
- Delete or Redact
- Hash or Tokenize
- Pseudonymize & Restore
- Random Generate or Select
- Custom (New Field) Functions
- Eclipse IDE
- Command Line
- Batch/Shell Scripts
- Ad Hoc or Scheduled
- In-situ/SQL Procedures
- System/API Library Calls
- Replication, Test & DevOps
- Incremental Update/Refresh
IRI Defines Startpoint SecurityListen Now
What Others Are Reading
Data Masking vs. Data Encryption
Do you know the differences between them? Learn about these two popular forms of data obfuscation and when to use them.Read Now
Which Masking Function is Best?
Read this review of the important decision criteria, including realism, reversibility, consistency, speed, and security.Read Now
PCI Tokenization in FieldShield
The Payment Card Industry Data Security Standard, or PCI DSS, requires encryption or tokenization of primary account numbers.Read Now
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?
- Do you need data masked the same way across different database and file formats?
- 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 deterministic (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?