In the ever-evolving landscape of data protection, the need for robust security measures has never been more critical. With the advent of regulations like the Protection of Personal Information Act (PoPIA), organizations find themselves under the spotlight, compelled to fortify their data security practices. While data encryption has emerged as a go-to solution for mitigating risks, it is essential to acknowledge that encryption alone does not provide a comprehensive answer to the complex challenges of data security and privacy.

The Limitations of Data Encryption

Data encryption, in its essence, is a powerful tool to safeguard sensitive information. It converts data into an unreadable format, ensuring that even if unauthorized individuals gain access to it, they cannot decipher its contents. This is particularly effective in preventing external breaches, where cybercriminals attempt to infiltrate an organization’s systems.

However, data encryption operates like a blunt instrument – it either shields all the data within its grasp or grants access to all of it. In the realm of data protection, a more nuanced and granular approach is often necessary.

PoPIA Condition 7 – Security Safeguards

PoPIA Condition 7, aptly named “Security Safeguards,” delineates the prerequisites for data protection under the act. It mandates that organizations must guarantee the integrity and confidentiality of personal information by implementing suitable and reasonable organizational and technical measures. While this is a significant step forward in data privacy, it’s important to recognize that Condition 7 cannot function in isolation.

Understanding the context of personal data becomes paramount in ensuring its protection. Consider a scenario where personal data is akin to a vault containing various valuable items. While your bank manager may legitimately require access to your credit history, a bank teller may not need such comprehensive access. Contextual access control is key to effective data protection.

The Rising Internal Threat

In recent times, incidents of internal abuses of protected data have become alarmingly frequent. Take, for instance, the case of Absa, where an employee “unlawfully made selected customer data available to a small number of external parties.” Unfortunately, such incidents are not isolated; they exemplify the growing risk posed by internal threats – the illegitimate use of data by authorized personnel.

Effectively safeguarding data in such an environment necessitates a multi-faceted approach.

The Challenge of Data Warehousing

Many organizations are shifting towards self-service Business Intelligence (BI) and are implementing enterprise data warehouses to support this transformation. They have formulated policies for classifying and accessing sensitive data, taking steps to identify and categorize such data elements.

However, challenges arise when it comes to building the data warehouse in a manner that restricts access to sensitive data across multiple levels. Sensitive data is often scattered throughout the warehouse, making encryption an impractical solution.

Let’s look at a real-world example.

An organisation we have been working with is implementing a new enterprise data warehouse as an enabler for self-service BI. They have defined policies and have taken steps to identify and classify sensitive data elements.

Building the data warehouse in such a way as to restrict access to (various) levels of sensitive data is where their challenges have come in. Sensitive data is spread throughout the warehouse.

Encryption cannot help.

One approach is to (try to) design the warehouse in such a way that sensitive data is separated into separate views. This means creating multiple views of the same data, each including data of various classifications. As one can imagine, this is non-trivial.

There has to be a better way.

Dynamic Access Management: A Nuanced Approach

In the quest for better data security, dynamic access management emerges as a game-changer. It provides role-based access control at the attribute level, offering a more nuanced and context-aware approach to data protection.

But what does this entail?

Policies become the guiding light for access control. By leveraging data governance principles, organizations can identify sensitive data in its context and apply different access permissions based on factors like the role of the person accessing the data, their location, and the classification of individual data elements.

The real magic lies in the dynamic adjustment of attribute visibility. Instead of merely encrypting all data, dynamic access management allows for the application of dynamic tokens or masks to individual attributes. For instance, one user may see a complete telephone number, while another might see only the last four digits, and yet another may not see the telephone number at all. This granular approach ensures that data access is limited according to the specific processing requirement, significantly reducing the risk of misuse.

The Power of Automation

A crucial aspect of dynamic access management is its ability to apply policies and access rules seamlessly across multiple systems and attributes. This automation streamlines the process, making it efficient and scalable.

In the scenario we previously explored, dynamic access management would enable the sharing of one dataset across various users and geographical locations with a single, well-thought-out design. This approach not only enhances security but also frees up analytics teams to focus on adding value without introducing unnecessary risk.

In conclusion, while data encryption remains a vital component of data security, it should not be viewed as the sole solution. The dynamic access management approach offers a more nuanced and effective way to protect sensitive data. By implementing role-based access controls at the attribute level and automating the enforcement of policies, organizations can enhance data security and privacy in the era of data protection.

So, the next time you’re faced with a data security challenge, remember that not every problem is a nail, and you don’t always need a hammer. Dynamic access management provides the toolbox needed to address data security with precision and finesse.

---

Disclaimer: This article is for informational purposes only and should not be construed as legal or professional advice. Organizations should consult with legal and data security experts to ensure compliance with relevant data protection regulations.

Photo by Fausto Marqués on Unsplash