Protect data in a Zero Trust world
Contoso Ltd. continues to expand its cloud usage and AI services. As users access sensitive data from different locations and devices, traditional perimeter-based security models aren't enough to protect that data. Zero Trust provides a more effective approach by assuming that no user, device, or service should automatically be trusted, even inside the corporate network.
With Zero Trust, security teams verify every access request, apply least privilege, and continuously monitor activity to protect sensitive information.
Traditional security models fall short
Older security models focused on protecting the corporate network perimeter. Once users were inside the network, they often had broad access to systems and data. This model no longer works when users work remotely, use personal devices, or collaborate across cloud platforms.
Without controls that verify users, devices, and access requests, sensitive data can be exposed even if attackers bypass the perimeter.
Zero Trust security principles
Zero Trust shifts the security model from assuming trust to always verifying trust. Core principles include:
- Verify explicitly: Always authenticate users and devices based on all available signals, such as identity, location, device health, and behavior.
- Use least privilege access: Limit users to only the data and resources they need for their roles.
- Assume breach: Design security strategies with the expectation that breaches can happen. Continuous monitoring and risk-based controls help detect and contain incidents early.
Applying Zero Trust to data protection
Zero Trust applies to more than just network access. It also protects sensitive data across cloud services, endpoints, and AI platforms. Key data protection actions include:
- Classifying and labeling sensitive data so policies apply wherever data resides.
- Applying encryption and rights management to control who can view or share sensitive content.
- Using data loss prevention (DLP) policies to prevent unauthorized sharing or transfers of sensitive data.
- Using insider risk management policies to identify potential actions that could lead to data exposure.
- Applying AI security controls to protect sensitive data used in AI applications.
By using Zero Trust principles, organizations protect sensitive data regardless of where users work, what devices they use, or how data moves across services.