how to mask fields which is part of a paragraph as request and response for Connect rules
Hi,
I have requirement to develop as below. when we during API call we need to mask PHI fields for request/Response , also both request and response are type of Paragraph.
Please let me know if any one has any ideas/designs for the above.
***Edited by Moderator Rupashree to add Capability tags***
Accepted Solution
Updated: 26 Feb 2024 10:18 EST
Pegasystems Inc.
GB
To mask sensitive data during an API call in Pega, you can use the Pega GenAI™ capabilities. Here are the steps:
- Create a Connect Generative AI Rule. This rule defines the request prompt that the system sends to Pega GenAI. You can customize this rule according to your needs.
- When creating the Connect Generative AI Rule, select the 'Mask sensitive data' checkbox. This will hide sensitive data in the request prompt before it is sent to the AI provider.
- The system applies the default configuration of the pyGenAIPIIdetector Rule to the request prompt. This rule recognizes entities such as email IDs, account numbers, names, and phone numbers, and masks them.
- The system sends the prompt request with the masked entities to Pega GenAI.
- After receiving the response from Pega GenAI, the system replaces the masked entities with the original values.
Please note that you are responsible for ensuring that client private data is protected as required by the applicable laws.
⚠ This is a GenAI-powered tool. All generated answers require validation against the provided references.
Creating a Connect Generative AI Rule
To mask sensitive data during an API call in Pega, you can use the Pega GenAI™ capabilities. Here are the steps:
- Create a Connect Generative AI Rule. This rule defines the request prompt that the system sends to Pega GenAI. You can customize this rule according to your needs.
- When creating the Connect Generative AI Rule, select the 'Mask sensitive data' checkbox. This will hide sensitive data in the request prompt before it is sent to the AI provider.
- The system applies the default configuration of the pyGenAIPIIdetector Rule to the request prompt. This rule recognizes entities such as email IDs, account numbers, names, and phone numbers, and masks them.
- The system sends the prompt request with the masked entities to Pega GenAI.
- After receiving the response from Pega GenAI, the system replaces the masked entities with the original values.
Please note that you are responsible for ensuring that client private data is protected as required by the applicable laws.
⚠ This is a GenAI-powered tool. All generated answers require validation against the provided references.
Creating a Connect Generative AI Rule
Masking sensitive data for use with AI > Changing the configuration of the masking Rule { .section}
Updated: 16 Feb 2024 5:02 EST
Pegasystems Inc.
GB
It is possible to mask sensitive data in the request and response for Connect rules in Pega Platform. However, the masking process is typically applied to specific recognized entities such as email IDs, account numbers, names, and phone numbers. If your Paragraph type request and response contain these types of entities, they can be masked. However, the mechanism to mask sensitive data does not guarantee that private data is protected. You, and not Pega, are responsible for ensuring that client private data is protected as required by the applicable laws.
⚠ This is a GenAI-powered tool. All generated answers require validation against the provided references.
Masking sensitive data for use with AI
If this is not helpful, please clarify your request further.
Virtusa Corp.
LK
Thanks for the Reply.
but still I am not clear how to Use Gen AI to mask the request for Connect Rest rule integration. Could you please explain on the steps
Regards,
Risvana
Accepted Solution
Updated: 26 Feb 2024 10:18 EST
Pegasystems Inc.
GB
To mask sensitive data during an API call in Pega, you can use the Pega GenAI™ capabilities. Here are the steps:
- Create a Connect Generative AI Rule. This rule defines the request prompt that the system sends to Pega GenAI. You can customize this rule according to your needs.
- When creating the Connect Generative AI Rule, select the 'Mask sensitive data' checkbox. This will hide sensitive data in the request prompt before it is sent to the AI provider.
- The system applies the default configuration of the pyGenAIPIIdetector Rule to the request prompt. This rule recognizes entities such as email IDs, account numbers, names, and phone numbers, and masks them.
- The system sends the prompt request with the masked entities to Pega GenAI.
- After receiving the response from Pega GenAI, the system replaces the masked entities with the original values.
Please note that you are responsible for ensuring that client private data is protected as required by the applicable laws.
⚠ This is a GenAI-powered tool. All generated answers require validation against the provided references.
Creating a Connect Generative AI Rule
To mask sensitive data during an API call in Pega, you can use the Pega GenAI™ capabilities. Here are the steps:
- Create a Connect Generative AI Rule. This rule defines the request prompt that the system sends to Pega GenAI. You can customize this rule according to your needs.
- When creating the Connect Generative AI Rule, select the 'Mask sensitive data' checkbox. This will hide sensitive data in the request prompt before it is sent to the AI provider.
- The system applies the default configuration of the pyGenAIPIIdetector Rule to the request prompt. This rule recognizes entities such as email IDs, account numbers, names, and phone numbers, and masks them.
- The system sends the prompt request with the masked entities to Pega GenAI.
- After receiving the response from Pega GenAI, the system replaces the masked entities with the original values.
Please note that you are responsible for ensuring that client private data is protected as required by the applicable laws.
⚠ This is a GenAI-powered tool. All generated answers require validation against the provided references.
Creating a Connect Generative AI Rule
Masking sensitive data for use with AI > Changing the configuration of the masking Rule { .section}