Project overview

• Design and implement an intelligent framework for automated document classification, labelling, and protection using AI and Data Loss Prevention (DLP) policies.
• The goal is to enhance data governance, ensure compliance with regulatory standards (e.g., GDPR), and prevent unauthorized data exposure.
• Number of interns: 01
• Project Ref: CED-BI/SECURITY-002

Key components & technologies

• AI models for content-based classification and sensitivity detection; integration with AI/ML frameworks.
• Data cataloging and labelling workflows tied to Microsoft Information Protection and Azure Information Protection.
• DLP policies to enforce protection rules across Microsoft 365 and other platforms, leveraging Microsoft 365 Compliance Center and Microsoft Graph API.
• Automation and scripting using PowerShell and Python to deploy and manage policies and labels.

Responsibilities & tasks

• Research, design and prototype AI-driven document classification models capable of sensitivity detection across document types.
• Implement automated labelling and data-cataloguing pipelines to apply consistent sensitivity labels at scale.
• Configure and test DLP rules in Microsoft 365 Compliance Center to enforce protection and prevent data leaks.
• Integrate solutions with Azure Information Protection and use Microsoft Graph API for policy/reporting automation.
• Develop PowerShell/Python scripts for deployment, monitoring and remediation workflows.

Expected outcomes & deliverables

• Automated and scalable document classification solution with demonstrable accuracy metrics.
• Consistent application of sensitivity labels across a sample dataset and documentation of labelling rules.
• Real-time protection mechanisms and DLP configurations that show prevention of simulated data leaks.
• Implementation report, deployment scripts, test cases, and recommendations for audit readiness and compliance.

Required skills & knowledge

• Microsoft Information Protection, Microsoft 365 Compliance Center, Azure Information Protection.
• AI/ML Frameworks and experience building or adapting models for text/content classification.
• Familiarity with Data Governance Tools and DLP concepts.
• Scripting/programming: PowerShell and Python; experience with Microsoft Graph API for automation.