Clean Rooms Are Just One Step Toward Secure Data Collaboration | Industry Insights | All MKC Content | ANA

Clean Rooms Are Just One Step Toward Secure Data Collaboration

By Sadegh Riazi

In an increasingly interconnected digital landscape, data collaboration has become a linchpin for business success. As cookie support declines and stringent privacy laws multiply, companies face the double-edged sword of needing more data collaboration and more data security. This has led to the rise of data clean rooms.

However, clean rooms are not the panacea they appear to be. They act as neutral containers for data collaboration, while collaborators onboard their data into these environments which introduces a series of data ownership, data movement, data security, and privacy issues.

The Limitations of Clean Rooms

As currently constituted, clean rooms present enterprises with a marginal improvement over sharing data directly with partners. There are still risks involved, because the data still must leave a brand's possession and then be decrypted on the other end. Furthermore, clean rooms offer very little interoperability. When they don't talk to each other, it increases the need for brands to manage data traffic. This means new engagements for every data process, escalating costs and creating friction.

In some cases, noise is being added to the data to reduce information leakage, but it also reduces accuracy and precludes one-to-one matching. The limited access control of clean rooms also restricts the functionality of marketers or data scientists. Furthermore, despite the promises made by clean room providers, they essentially operate on trust. If a clean room wishes to learn from the data, even during the onboarding process, it can do so. They can promise not to look, but there is no safeguard in place.

Secure Multi-Party Computation: The Future of Data Collaboration

This may all sound jarring to brands that have just invested heavily in clean room solutions, but, rest assured, there are paths forward.

Secure Multiparty Computation (SMPC) is a subfield of cryptography that enables parties to run analytics over their data while keeping those inputs private. In simpler terms, it allows multiple parties to collaborate on data without having to reveal their individual data sets and without the data ever leaving its own environments.

Brands can then conduct data collaboration securely, without the need to trust a third-party custodian. This reduces both the risk of data exposure and the friction that comes with managing multiple clean room engagements. By enabling SMPC as a collaboration software, and not a platform, allows companies to directly work together while maintaining full data ownership.

Furthermore, SMPC opens the door to interoperability, finally solving the issues that come with clean rooms not talking to each other. This paves the way for large-scale, efficient, and effective data collaboration while upholding consumer privacy and data security.

The Need for Data Collaboration Is Here to Stay

The need for more secure and effective data collaboration will only grow with time. While clean rooms have served a purpose, it's clear that the future lies in embracing and advancing technologies like SMPC that combine the collaborative components with greater data security.

As we move forward, the ad industry's focus should be on fostering innovations in secure computing and cryptography. By doing so, we can revolutionize the way that brands collaborate on data, ensuring privacy, security, and control. Clean rooms have been a step on this journey, but the road ahead promises far more exciting developments. Let's step confidently into the future of secure computing.

The views and opinions expressed are solely those of the contributor and do not necessarily reflect the official position of the ANA or imply endorsement from the ANA.

Sadegh Riazi is founder and CEO at Pyte.