- What's New
- Function Overview
- Service Overview
- Billing
- Getting Started
-
User Guide
- Service Provisioning
- Allowing or Disallowing Access to Cloud Assets
- Asset Map
- Asset Management
- Sensitive Data Identification
- Data Asset Protection
- Data Security Operations
- Alarm Notifications
- Permissions Management
- Key DSC Operations
- Best Practices
-
API Reference
- Before You Start
- Calling APIs
-
API Description
- Data Watermarking
- Resource Management
- Dynamic Data Masking
- Alarm Notifications
-
Image Watermarking
- Injecting Invisible Watermarks into Images
- Extracting Invisible Text Watermarks
- Extracting Invisible Watermarks from Images
- Injecting Invisible Watermarks into Images (Image Addresses)
- Extracting Dark Watermarks from Images (Image Addresses)
- Extracting Invisible Image Watermarks from Images (Image Addresses)
- Asset Management
- Document Watermarking
-
Sensitive Data Discovery
- Querying the Identification Task List
- Querying the Result of an Identification Task
- Viewing the Rule List
- Creating a Sensitive Data Scanning Rule
- Modifying a Sensitive Data Scanning Rule
- Deleting a Sensitive Data Scanning Rule
- Querying Sensitive Data Scanning Rule Groups
- Creating a Sensitive Data Scanning Rule Group
- Deleting a Sensitive Data Scanning Rule Group
- Creating a Sensitive Data Scanning Task
- Deleting a Sensitive Data Scanning Task
- Static Data Masking
- API Call Records
- Appendixes
- Change History
- SDK Reference
-
FAQs
- Product Consulting
- Regions and AZs
- Asset Authorization
-
Sensitive Data Identification and Masking
- What Services Can Use DSC to Scan for Sensitive Data?
- How Long Does It Take for DSC to Identify and Mask Sensitive Data?
- What Are the Identification Templates Supported by DSC?
- Does Data Masking Affect My Raw Data?
- Does DSC Have Specific Requirements on the Character Set for Which Sensitive Data Is to Be Identified and Masked?
- Data Watermarking
- Data Usage Audit
Overview
If data leakage occurs, you can use DSC to extract the watermark information. In this case, the organization or person that is accountable for the leakage problem can be easily found. Adding watermarks does not affect the distributed data usage.
Database Type |
Data Type |
---|---|
DWS |
smallint, integer, bigint, float4, float8, varchar, text, and char |
MRS-HIVE |
smallint, int, long, float, double, and string |
Type |
Format |
---|---|
Document |
pdf, pptx, docx, and xlsx |
Images (invoking image watermark APIs) |
*.jpg, *.jpeg, *.jpe, *.png, *.bmp, *.dib, *.rle, *.tiff, *.tif, *.ppm, *.webp, *.tga, *.tpic, and *.gif |
JSON data (invoking data watermark APIs) |
The value can be an integer, floating-point number, or string. |
Application Scenarios
Data watermarking is widely used in government departments, healthcare agencies, finance institutions, academic institutes, and other organizations. It is generally used for copyright protection and source tracing.
- Data copyright protection: In scenarios where digital works are downloaded or copied for use and database services (data mining and analysis) provide data to third parties, digital watermarks can be used to identify the copyright when disputes occur,
- Source tracing: Data provided for internal employees or third parties can be injected with watermarks to identify the ownership and remind them of keeping the data secure. When the data leaked, the watermarks can be used to trace the source of data leak and identify the root cause.
Advantages and Highlights
- Visible and invisible watermarks: You can inject visible or invisible watermarks into the data as needed to efficiently cope with data theft through image process tools, picture taking, or screenshots.
- Detectable and tamper-proofing: Watermarks injected into the data can be detected and will not be lost, fabricated, and tampered with.
- High robustness: Watermarks are not easily removed during transmission or use. Even if the data carrier is tampered with or damaged, there is a high probability that watermarks are extracted.
Procedure
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