Adopting a Zero-Trust Model for Secure Data Access and Management

Zero Trust Model

Zero-trust security has gained traction in a world where no one can be trusted. It is hardly surprising that spending on zero-trust will rise significantly, given that breaches are at an all-time high and cyber-attacks are becoming increasingly sophisticated.

With the rise of the new distributed and hybrid workforce worldwide that logs on remotely, users often do not access applications or data from a specific network segment. A new security architecture is also required when more apps and data are SaaS-based or otherwise not contained within a particular network perimeter.

Since different businesses have different objectives, priorities, and stages of data accessibility maturity, there is no one approach to establishing and executing zero-trust security policies. For instance, while some companies are adopting a “need to share” security policy, others are enforcing “need to know” standards.

A Unified Zero-Trust Strategy for Data Access

As part of their data protection strategy, businesses should consider a unified, zero-trust approach to data access for various reasons, both in terms of risk and value.

Since sensitive information is typically stored in databases, data lakes, or data warehouses, it is crucial that every business considers how to manage and secure access to all sensitive data across all of its distributed environments.

In many cases, companies are dealing with an increase in the number of data users, which presents a great opportunity to increase business value and security risk because fewer restrictions are being placed on who can access sensitive data and when.

To ensure that data is stored, used, processed, and shared securely, each company has to have clear data access and security policies.

Implementing a Continuous and Unified Zero-Trust Approach for Data Access

No matter how an organization chooses to implement the zero-trust model – to adhere to it, all organizations must continuously authorize, authenticate, and validate users across all data sources.

  • Continuous Authentication 

Many methods of authentication are available, including key-pair authentication, database credentials, and Single Sign-On (SSO) with an Identity Provider. The universal truth is that all businesses must ensure that data in production is accessible to all data analysts.

To access production data, most businesses either allow continuous access to the data or require a single user to sign in on behalf of other users within a specific department. Giving temporary access to the data as needed is the practical zero-trust solution in this situation.

  • Continuous Authorization

Authorization is a big challenge, especially at scale. On the one hand, corporations take on more security risks the more data they authorize. However, they want users to have access to all the data they need.

Implementing real-time authorization depending on the various demands of the data consumers and consolidating authentication across platforms are some of the practical ways to execute zero-trust authorization.

To do this, it is necessary to gain a good understanding of the many datasets each user has access to, request and provide access in real-time, and manage temporary access or access that is no longer required by invalidating it across data stores.

Also Read: Strategies to Develop a Zero-Trust Cyber Security Strategy

  • Continuous Validation 

Applying anonymization policies, such as data localization and data masking regulations, among others, are examples of this form of validation. From there, businesses need to figure out how to consistently apply their data security policies across all data platforms and data access points.

A unified approach to data access policies can ensure that they are consistently enforced and also help monitor and audit data access policies in real time for any new or hidden threats and to respond appropriately to compliance and privacy standards.

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