- PrivaceraCloud Release 4.5
- PrivaceraCloud User Guide
- PrivaceraCloud
- What is PrivaceraCloud?
- Getting Started with Privacera Cloud
- User Interface
- Dashboard
- Access Manager
- Discovery
- Usage statistics
- Encryption and Masking
- Privacera Encryption core ideas and terminology
- Encryption Schemes
- Encryption Schemes
- System Encryption Schemes Enabled by Default
- View Encryption Schemes
- Formats, Algorithms, and Scopes
- Record the Names of Schemes in Use and Do Not Delete Them
- System Encryption Schemes Enabled by Default
- Viewing the Encryption Schemes
- Formats, Algorithms, and Scopes
- Record the Names of Schemes in Use and Do Not Delete Them
- Encryption Schemes
- Presentation Schemes
- Masking schemes
- Create scheme policies on PrivaceraCloud
- Encryption formats, algorithms, and scopes
- Deprecated encryption formats, algorithms, and scopes
- PEG REST API on PrivaceraCloud
- PEG API Endpoint
- Request Summary for PrivaceraCloud
- Prerequisites
- Anatomy of a PEG API endpoint on PrivaceraCloud
- About constructing the datalist for /protect
- About deconstructing the response from /unprotect
- Example of data transformation with /unprotect and presentation scheme
- Example PEG REST API endpoints for PrivaceraCloud
- Audit details for PEG REST API accesses
- Make calls on behalf of another user on PrivaceraCloud
- Privacera Encryption UDF for masking in Databricks
- Privacera Encryption UDFs for Trino
- Syntax of Privacera Encryption UDFs for Trino
- Prerequisites for installing Privacera Crypto plug-in for Trino
- Variable values to obtain from Privacera
- Determine required paths to crypto jar and crypto.properties
- Download Privacera Crypto Jar
- Set variables in Trino etc/crypto.properties
- Restart Trino to register the Privacera Crypto UDFs for Trino
- Example queries to verify Privacera-supplied UDFs
- Azure AD setup
- Launch Pad
- Settings
- General functions in PrivaceraCloud settings
- Applications
- About applications
- Azure Data Lake Storage Gen 2 (ADLS)
- Athena
- Privacera Discovery with Cassandra
- Databricks
- Databricks SQL
- Dremio
- DynamoDB
- Elastic MapReduce from Amazon
- EMRFS S3
- Files
- File Explorer for Google Cloud Storage
- Glue
- Google BigQuery
- Kinesis
- Lambda
- Microsoft SQL Server
- MySQL for Discovery
- Open Source Spark
- Oracle for Discovery
- PostgreSQL
- Power BI
- Presto
- Redshift
- Redshift Spectrum
- Kinesis
- Snowflake
- Starburst Enterprise with PrivaceraCloud
- Starburst Enterprise Presto
- Trino
- Datasource
- User Management
- API Key
- About Account
- Statistics
- Help
- Apache Ranger API
- Reference
- Okta Setup for SAML-SSO
- Azure AD setup
- SCIM Server User-Provisioning
- AWS Access with IAM
- Access AWS S3 buckets from multiple AWS accounts
- Add UserInfo in S3 Requests sent via Dataserver
- EMR Native Ranger Integration with PrivaceraCloud
- Spark Properties
- Operational Status
- How-to
- Create CloudFormation Stack
- Enable Real-time Scanning of S3 Buckets
- Enable Discovery Realtime Scanning Using IAM Role
- How to configure multiple JSON Web Tokens (JWTs) for EMR
- Enable offline scanning on Azure Data Lake Storage Gen 2 (ADLS)
- Enable Real-time Scanning on Azure Data Lake Storage Gen 2 (ADLS)
- How to Get Support
- Coordinated Vulnerability Disclosure (CVD) Program of Privacera
- Shared Security Model
- PrivaceraCloud
- PrivaceraCloud Previews
- Privacera documentation changelog
What is PrivaceraCloud?
PrivaceraCloud is a Software-as-a-Service (SaaS) data access governance and enforcement management platform. It works with a wide range of datasources/applications, including AWS and Azure based datasources/applications.
PrivaceraCloud manages and controls access to sensitive data. It enables:
Central definition and management of fine-grained access control policies across multiple cloud services
Data access audits
Compliance, audit, and governance reports
Encryption, decryption, and masking
Key Features
Data Access Management based on ABAC (Attribute-Based Access Control) and RBAC (Role-Based Access Control) policies.
Resource-based (physical and logical metadata) data classification.
Tag-based data classification (business metadata).
Comprehensive normalized audits with rich event metadata detailing who, what, when, and where.
Reports and dashboards
Basic Concepts
Restrictions to access are configured using data access policies which are comprised of rules. Rules specify which users and groups can access what data.
A useful PrivaceraCloud account has three parts: Applications, data access users, and data access policies.
About applications, which must be connected to PrivaceraCloud. Three different data access methods are for this connection Data access methods.
Data access users requiring access to the connected resources. These users can be defined individually within PrivaceraCloud using About data access users, groups, and roles resource policies
Users and Groups can also be imported from an a user directory service such as LDAP/AD or UserSync.
Policies define the relationship between the data resources and the data access users. Policy rules are established and managed in Resource Policies and Tag Policies.
How PrivaceraCloud Works
PrivaceraCloud works with and extends Apache Ranger to provide data access governance with centralized management of authorization policies and auditing. Policy enforcement points for access control run in your AWS or Azure environment. PrivaceraCloud policies are distributed to and synchronized with these policy enforcement points. These distributed enforcement points log all audit information back to your PrivaceraCloud account.