For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
HUMAN DashboardHUMAN WebsiteRequest a Demo
Product GuidesEnforcer GuidesMobile SDKAPI ReferenceCustomer support
Product GuidesEnforcer GuidesMobile SDKAPI ReferenceCustomer support
  • Getting Started
    • Overview
    • Best practices
  • Sightline Cyberfraud Defense
    • About Sightline Cyberfraud Defense
    • Getting Started
    • What's different in Sightline Cyberfraud Defense
    • Sensor changelog
    • About the Overview Dashboard
    • Glossary
  • AgenticTrust
    • Getting started with AgenticTrust
    • AI Agents Monitoring Dashboard
    • AI Visitors Overview Dashboard
    • Manage AI Agent Permissions
    • Agentic Activity Priority
    • Agent Trust Levels
  • Account Defender
    • Account Defender Overview
    • Use Cases
    • Prerequisites
    • Getting Started with Account Defender
    • Optimizing Account Defender Detection
    • Validating Account Defender Integration
    • Risk Triggers
    • About Network Events
    • Troubleshooting
  • Bot Defender
    • Bot Defender Overview
    • Detection
    • Bot Defender Policy Settings
    • Footprint
  • Credential Intelligence
    • Credential Intelligence Overview
    • How to Access the Breached Flag
    • Credential Intelligence FAQ
    • Credential Intelligence Dashboard
  • Code Defender
    • Code Defender Introduction
    • Getting Started with Code Defender
    • Code Defender Glossary
    • Website Risk Analyzer
  • Platform
    • Account settings
    • Manage users
    • Role permissions
    • Enforcer configurations
      • Adobe Experience Platform
      • Auth0
      • AWS S3
      • Datadog
      • Email to Consumer
      • GCS
      • HTTP webhook
      • Okta
      • Slack
      • Splunk
      • Sumo Logic
      • Syslog
    • Page Type Mapping
  • Client-Side Integration
    • JavaScript tag
    • Improving first page performance
    • Use of cookies & web storage
    • Advanced client integration
LogoLogo
Login
Login
HUMAN DashboardHUMAN WebsiteRequest a Demo
On this page
  • Prerequisites
  • Integrate with Adobe Experience Platform
  • Create an Adobe Experience Data Model schema
  • Create a dataset from the schema
  • Create a dataflow with the dataset
  • Set up the Adobe Experience Platform integration in HUMAN
PlatformIntegrations

Adobe Experience Platform integration

Was this page helpful?
Previous

Auth0 integration

Next
Built with
Data export

You can integrate Sightline Cyberfraud Defense with the Adobe Experience Platform to set your HUMAN data exports as a data source in the Adobe Experience Platform Data Lake. You can then use your HUMAN traffic data throughout Adobe’s product suite for further investigation and analysis for your organization.

You can use the Adobe Experience Platform integration to create a data export.

Prerequisites

  • An Adobe Experience Platform account with permissions to configure schemas and data sources
  • Appropriate role permissions to create and manage integrations
  • Download HUMAN’s data schema CSV, which you’ll need while setting up an Adobe schema.

Integrate with Adobe Experience Platform

1

Create an Adobe Experience Data Model schema

First, you need to create an Adobe Experience Data Model (XDM) schema with HUMAN’s data export values to map to. To do so, follow the steps in Adobe’s Machine learning-assisted schema creation article while using the following HUMAN specifications:

  1. In Select a base class, choose Other. Then, click Create class and create a new class with the following (see Adobe’s Create and edit classes in the UI article for more on creating classes):
    • Display name: Human Activity Data
    • Behavior: Record
  2. In Upload a CSV file, upload the HUMAN CSV file provided in the prerequisites.
  3. In Preview data, confirm each Source Field has a new Field Group. Typically, new Field Groups follow the pattern New Field Group YYYY-MM-DD_aa11bb.
  4. If a Source Field doesn’t have a new Field Group, edit each field so that:
    • The Target Field and Display Name match the Source Field
    • The Field Group is set to New Field Group YYYY-MM-DD_aa11bb.
  5. In Name and save schema, confirm there’s only one field group, then set the Schema display name to “HUMAN data”. Then, click Finish.
2

Create a dataset from the schema

Next, you need to create a dataset in Adobe based off of the HUMAN data schema you created in Part 1. To do so, the instructions in Adobe’s Datasets user guide > Create a dataset with an existing schema and name it HUMAN-Adobe-integration-dataset.

3

Create a dataflow with the dataset

Now, you need to create an Adobe dataflow using the HUMAN-Adobe-integration-dataset you created in Part 2. To do so, follow the instructions in Adobe’s Create an HTTP API streaming connection using the UI while using the following HUMAN specifications:

  1. Create a streaming connection with a new account with the following:
    • Account name: Any name you’ll recognize while setting up the integration
    • Streaming account requires authentication: If you’d like to authenticate this connection, toggle this on. This also generates an OAuth token that you’ll need to provide to HUMAN later on in this process.
    • Data is XDM schema compatible: Check this box to confirm data is XDM compatible.
  2. Skip Adobe’s Select data step. This isn’t relevant since you’re using XDM-compatible data.
  3. In Map data fields to an XDM schema > Use an existing dataset, select an Existing dataset and choose the HUMAN-Adobe-integration-dataset you made in Part 2.
  4. Skip the remaining steps until Review. Confirm everything is correct, then click Finish.
4

Set up the Adobe Experience Platform integration in HUMAN

Finally, you need to create an Adobe Experience Platform integration in the HUMAN portal and connect it to the Adobe schema, dataset, and dataflow you created in the previous parts.

  1. Navigate to Platform Settings > Integrations and click the Adobe Experience Platform integration.
  2. Click Add Integration.
  3. Provide the following:
    • Integration name: How the integration will appear in your HUMAN account.
    • Streaming Endpoint URL: The full Streaming endpoint for the dataflow you created in Part 3. You can find this by navigating to the Adobe Experience Platform > Connections > Sources and clicking the dataflow you created in Part 3.
    • Schema URL: The full Schema ID for the HUMAN data schema you created in Part 1. You can find this by navigating to the Adobe Experience Platform > Data Management > Schema and selecting the Human data schema.
    • Dataflow ID: The full Dataflow ID from the dataflow you created in Part 3. You can find this by navigating to the Adobe Experience Platform > Connections > Sources > select the dataflow you created in Part 3.
    • Dataset ID: The full Dataset ID from the dataflow you created in Part 3. You can find this by navigating to the Adobe Experience Platform > Connections > Sources > select the dataflow you created in Part 3.
    • Org ID: The Current Org ID, which is the ID with 24 characters and includes @Adobeorg. See Adobe’s Organizations and account linking article for details on how to find this ID.
    • Auth token (optional): The OAuth token generated if you created a dataflow with authentication in Part 3. You can find this in your Adobe Developer Console.
  4. Click Test Connection.
  5. Once the test succeeds, click Save changes.

You have successfully configured an Adobe Experience Platform integration. Next, make sure to use the integration to create a data export.