Secure and Govern Azure AI Services
AI and the need to secure organizational data
Data overexposure
Data used by AI could be sensitive, including PII and PHI and could violate patient's privacy rights
Loss of customer trust
Data loss
Data produced by AI may be vulnerable to unauthorized access or disclosure by malicious actors
Diminished competitive edge
Data compliance
Data used and produced by AI may not comply with relevant regulations and AI ethics principles
Heavy penalties
Fortify data security with an integrated approach
- Discover and auto-classify data and prevent it from unauthorized use across apps, services, and devices
- Understand the user intent and context around sensitive data to identify the most critical risks
- Enable Adaptive Protection to assign appropriate DLP policies to high-risk users
Enable Adaptive Protection with Microsoft Purview
Optimize data protection automatically
- Context-aware detection
Identify the most critical risks with ML-driven analysis of both content and user activities - Dynamic controls
Enforce effective controls on high-risk users while others maintain productivity - Automated mitigation
Minimize the impact of potential data security incidents and reduce admin overhead
Sensitivity labels span your entire data estate
- They are a representation of your information taxonomy
- They describe the priority assigned to your categories of sensitive information.
