- PrivaceraCloud Release 7.4
- Enhancements and updates in PrivaceraCloud release 7.4
- Known Issues in PrivaceraCloud 7.4
- PrivaceraCloud User Guide
- Overview of PrivaceraCloud
- Connect applications with the setup wizard
- Connect applications
- About applications
- Connect Azure Data Lake Storage Gen 2 (ADLS) to PrivaceraCloud
- Connect Amazon Textract to PrivaceraCloud
- Athena
- Privacera Discovery with Cassandra
- Connect Databricks to PrivaceraCloud
- Databricks SQL
- Databricks SQL Overview and Configuration
- Planning and general process
- Prerequisites
- Databricks SQL with Privacera Hive
- Connect Databricks SQL application
- Grant Databricks SQL permissions to PrivaceraCloud users
- Define a resource policy
- Test the policy
- Databricks SQL PolicySync fields
- Configuring column-level access control
- View-based masking functions and row-level filtering
- Create an endpoint in Databricks SQL
- Databricks SQL Fields
- Databricks SQL Hive Service Definition
- Databricks SQL Masking Functions
- Databricks SQL Encryption
- Use a custom policy repository with Databricks
- Connect Databricks SQL to Hive policy repository on PrivaceraCloud
- Databricks SQL Overview and Configuration
- Connect Databricks Unity Catalog to PrivaceraCloud
- Connect S3 to PrivaceraCloud
- Prerequisites in AWS console
- Connect S3 application to PrivaceraCloud
- Enable Privacera Access Management for S3
- Enable Data Discovery for S3
- S3 AWS Commands - Ranger Permission Mapping
- S3
- AWS Access with IAM
- Access AWS S3 buckets from multiple AWS accounts
- Add UserInfo in S3 Requests sent via Dataserver
- Control access to S3 buckets with AWS Lambda function on PrivaceraCloud
- Dremio Plugin
- DynamoDB
- Connect Elastic MapReduce from Amazon application to PrivaceraCloud
- Connect EMR application
- EMR Spark access control types
- PrivaceraCloud configuration
- AWS IAM roles using CloudFormation setup
- Create a security configuration
- Create EMR cluster
- How to configure multiple JSON Web Tokens (JWTs) for EMR
- EMR Native Ranger Integration with PrivaceraCloud
- Connect EMRFS S3 to PrivaceraCloud
- Files
- GBQ
- Google Cloud Storage
- Connect Glue to PrivaceraCloud
- Google BigQuery for PolicySync
- Connect Kinesis to PrivaceraCloud
- Connect Lambda to PrivaceraCloud
- Microsoft SQL Server
- MySQL for Discovery
- Open Source Apache Spark
- Oracle for Discovery
- PostgreSQL
- Connect Power BI to PrivaceraCloud
- Presto
- Redshift
- Snowflake
- Starburst Enterprise with PrivaceraCloud
- Starburst Enterprise Presto
- Trino
- Connect users
- Data access Users, Groups, and Roles
- UserSync
- Portal user LDAP/AD
- Datasource
- Okta Setup for SAML-SSO
- Azure AD setup
- SCIM Server User-Provisioning
- User Management
- Identity
- Access Manager
- Access Manager
- Resource Policies
- Tag Policies
- Scheme Policies
- Service Explorer
- Reports
- Audit
- About data access users, groups, and roles resource policies
- Security zones
- Discovery
- Classifications via random sampling
- Privacera Discovery scan targets
- Propagate Privacera Discovery Tags to Ranger
- Enable offline scanning on Azure Data Lake Storage Gen 2 (ADLS)
- Enable Real-time Scanning of S3 Buckets
- Enable Real-time Scanning on Azure Data Lake Storage Gen 2 (ADLS)
- Enable Discovery Realtime Scanning Using IAM Role
- Encryption
- Overview of Privacera Encryption
- Encryption schemes
- Presentation schemes
- Masking schemes
- Create scheme policies
- Privacera-supplied encryption schemes for the Privacera API
- Privacera-supplied encryption schemes for the Bouncy Castle API
- API date input formats
- Deprecated encryption formats, algorithms, and scopes
- Privacera Encryption REST API
- PEG API endpoint
- PEG REST API encryption endpoints
- Prerequisites
- Common PEG REST API fields
- Construct the datalist for the /protect endpoint
- Deconstruct the response from the /unprotect endpoint
- Example data transformation with the /unprotect endpoint and presentation scheme
- Example PEG API endpoints
- Make encryption API calls on behalf of another user
- Privacera Encryption UDF for masking in Databricks on PrivaceraCloud
- Privacera Encryption UDFs for Trino on PrivaceraCloud
- Syntax of Privacera Encryption UDFs for Trino
- Prerequisites for installing Privacera Crypto plug-in for Trino
- Download and install Privacera Crypto jar
- Set variables in Trino etc/crypto.properties
- Restart Trino to register the Privacera encryption and masking UDFs for Trino
- Example queries to verify Privacera-supplied UDFs
- Privacera Encryption UDF for masking in Trino on PrivaceraCloud
- Encryption UDFs for Apache Spark on PrivaceraCloud
- Launch Pad
- Settings
- Dashboard
- Usage statistics
- Operational status of PrivaceraCloud and RSS feed
- How to Get Support
- Coordinated Vulnerability Disclosure (CVD) Program of Privacera
- Shared Security Model
- PrivaceraCloud Previews
- Preview: File Explorer for S3
- Preview: File Explorer for Azure
- Preview: File Explorer for GCS
- Preview: Scan Generic Records with NER Model
- Preview: Scan Electronic Health Records with NER Model
- Preview: OneLogin setup for SAML-SSO
- Preview: Azure Active Directory SCIM Server UserSync
- Preview: OneLogin UserSync
- Preview: PingFederate UserSync
- Quickstart for Databricks Unity Catalog on PrivaceraCloud
- What do I need to do in my Databricks Workspace?
- Where is the sample dataset in my Databricks Workspace?
- What should I do in the PrivaceraCloud web portal?
- Access use-case - How do I give a user access to a table or restrict from running a SQL select query?
- Access use-case - How do I restrict a user from seeing contents of a column in the result of a SQL select query?
- Column masking use-case - How do I restrict a user from seeing contents of a column by masking the values in the result of a SQL select query?
- Access use-case - How do I disallow a user from seeing certain rows of a table?
- PrivaceraCloud documentation changelog
Encryption UDFs for Apache Spark on PrivaceraCloud
This section describes how to install and configure the Privacera Crypto jar in Apache Spark to use Encryption UDFs to encrypt and decrypt data in Open Source Saprk.
Syntax of Privacera Encryption UDFs for Apache Spark
The Privacera Crypto jar includes the following encryption-related UDFs.
Encrypt: With the quoted '<encryption_scheme_name>'
, the protect
UDF encrypts all values of <column_name>
and writes the encrypted data to <new_column_name>
in <table_name>
:
select protect(<column_name>, <encryption_scheme_name>) as <new_column_name> from <database_name>.<table_name>;
Decrypt: With the quoted '<encryption_scheme_name>
', the unprotect
UDF decrypts all values of <column_name>
and writes the decrypted data to <new_column_name>
in <table_name>
:
select unprotect(<column_name>, '<encryption_scheme_name>') as <new_column_name> from <database_name>.<table_name>;
Decrypt with obfuscation: With the quoted '<encryption_scheme_name>
', the unprotect
UDF decrypts all values of <column_name>
, further obfuscates the decrypted data via <presentation_scheme_name>
, and writes the decrypted, obfuscated data to <new_column_name>
in <table_name>
:
select unprotect(<column_name>, '<encryption_scheme_name>', 'presentation_scheme_name') as <new_column_name> from <table_name>;
For example usage, see Example queries to verify UDFs
Download and install Privacera Crypto jar
To install the Privacera Crypto jar file in Apache Spark, get the URL of the Privacera Crypto jar file and download it to your Apache Spark, instance:
In your PrivaceraCloud account, go to Settings > API Key.
Under the PEG heading, for PEG Crypto Starburst Trino Jar, click COPY URL, and use that URL with
wget
on the command line of your Apache Spark instance. This URL is shown below as<Privacera_Crypto_Jar_URL>
.cd <path_to_apache_spark_home_directory> wget <Privacera_Crypto_Jar_URL> -O privacera-crypto-jar-with-dependencies.jar
Copy the jar file to your Apache Spark instance's
plugins/privcera
directory, which you should create if it does not already exist.
Set up in Apache Spark
After you have downloaded the Privacera Crypto jar, you need to set some properties, update your Apache Spark start-up script, and define the UDFs.
Set variables in Apache Spark conf/crypto.properties
Create a file in Apache Spark called <path_to_apache_spark_home_directory>/conf/crypto.properties
:
Add the following properties to the file, where:
The value of your endpoint for Privacera Encryption on PrivaceraCloud,
<PrivaceraCloud_Encryption_URL>
is obtained by clicking the Copy Url link in Settings > Api Key
privacera.crypto.native.threadpool.size=100 privacera.crypto.shared.secret=secret privacera.crypto.session.cache.size=1000 privacera.deployment.mode.saas=true privacera.peg.base.url=<PrivaceraCloud_Encryption_URL> privacera.peg.username=<PrivaceraCloud_Encryption_Username> privacera.peg.password=<PrivaceraCloud_Encryption_Password>
Add envar to spark-env.sh
Follow these commands to define the path to the Privacera Crypto jar:
vi <absolute_path_to_apache_spark_home_directory>/conf/spark-env.sh export CRYPTO_CONFIG_DIR=<absolute_path_to_apache_spark_home_directory>/conf
Restart Apache Spark
# Go to Apache Spark bin directory cd <absolute_path_to_trino_home_directory>/bin # Restart Apache Spark ./spark-sql
Create Privacera protect and unprotect UDFs
To create both Privacera protect and unprotect user-defined function (UDF), run the following SQL commands inApache Spark :
create database if not EXISTS privacera; drop function if exists privacera.protect; drop function if exists privacera.unprotect; drop function if exists privacera.mask; CREATE FUNCTION privacera.protect AS 'com.privacera.crypto.PrivaceraEncryptUDF'; CREATE FUNCTION privacera.unprotect AS 'com.privacera.crypto.PrivaceraDecryptUDF'; CREATE FUNCTION privacera.mask AS 'com.privacera.crypto.PrivaceraMaskUDF';
Example queries to verify UDFs
See the syntax detailed in Syntax of Privacera Encryption UDFs for Apache Spark.
Encrypt: The following example query with the protect
UDF encrypts the cleartext CUSTOMER_EMAIL
column of the CUSTOMERS
table using the quoted'EMAIL'
encryption scheme:
select protect(CUSTOMER_EMAIL, `EMAIL`) from CUSTOMERS;
Decrypt: The following example query with the unprotect
UDF decrypts the encrypted CUSTOMER_EMAIL
column of the CUSTOMERS
table using the quoted 'EMAIL'
encryption scheme:
select unprotect(CUSTOMER_EMAIL, 'EMAIL') from CUSTOMERS;
Decrypt with obfuscation: The following example query with the unprotect
UDF decrypts the encrypted CUSTOMER_EMAIL
column of the CUSTOMERS
table using the quoted 'EMAIL'
encryption scheme and obfuscates the decrypted data with the presentation scheme PRESENTATION_EMAIL
:
select unprotect(CUSTOMER_EMAIL, 'EMAIL', 'PRESENTATION_EMAIL') as OPTIONAL_OUTPUT_COLUMN_FOR_OBFUSCATED_DATA from CUSTOMERS;