Unlocking the Full Potential of Data Collaboration Through PETs

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Read more about author Alistair Bastian.

What’s the future of data collaboration? It’s a question that should be on the lips of every C-suite executive in global organizations right now. The unrealized potential of consumer data is immense for businesses wanting to forge deeper connections with their customers and unlock new opportunities, but many are unsure how to proceed when faced with the legal and reputational impacts of privacy violations.

The interlinked trends of growing legislative influences and consumer concerns about data privacy have fueled a surge of interest in privacy-enhancing technologies (PETs). While PETs are nothing new – they’ve been around for several decades now – the promise of extracting deeper insights without exposing raw customer data has obvious appeal to organizations of all types. 

In this blog post, I’ll outline how using the right blend of PETs can open up new possibilities through the principles of privacy-enhanced collaborative computing (PECC), and explain why privacy must be the foundation stone of data collaboration strategies for organizations that want to get the most out of their customer data.

The Potential of Data Collaboration

Data partnerships are necessary for businesses to flourish in the modern digital landscape. Through collaboration, organizations in a wide range of industries including (but not limited to) consumer goods, media, healthcare and finance can utilize data partnerships to enhance decision-making, unveil fresh opportunities, improve customer service, and cut costs.

These data-based partnerships can range from simple collaborations between two parties to more complex scenarios involving multiple parties. The gauge of success is whether the collaboration delivers a mutually agreed positive business outcome, while preserving complete control and limiting broader access to the proprietary datasets involved.

However, there are many obstacles to establishing effective partnerships. Technical aspects such as integration, system compatibility, data quality, and standardization must be considered. On top of this, navigating the labyrinth of legal and regulatory compliance can be intricate, costly, and time-intensive.

With businesses having moved much of their data into the cloud in recent years,  transferring, collecting, and processing sensitive or personal information involves ceding some control over its security to the cloud provider. The processing phase is especially risky. Data at rest is protected by encryption, while data in transit is protected by SSL/TLS (secure sockets layer and transport layer security). Data in use, though, is more vulnerable. The risks of data breaches or leaks, unauthorized access, and regulatory non-compliance come to a peak during this phase. For data collaborations to be successful, this is a key hurdle to overcome.

The Promise of Privacy-Enhanced Collaborative Computing

This is where PETs come into play. This group of tools has emerged to meet the needs of organizations that want to reap the benefits of dual- or multi-party data collaborations. While PETs can function independently, individually they tend to focus on solving a very specific problem. Implementing a single PET into an existing data collaboration platform is a complex task, and further deployments of other PETs into the platform would involve a similar challenge.

Organizations would be better off building their data collaboration system around a suite of PETs rather than applying a patchwork of individual tech integrations to their existing stack. Privacy and PETs must be ingrained as fundamental aspects, rather than retrospectively added. When embedded into the foundations of a collaboration platform, PETs enable powerful privacy-enhanced collaborative computing (PECC) capabilities. PECC is a facilitator of dynamic and efficient data collaborations that revolve around the principles of security, privacy, and trust. 

Trust is pivotal to successful relationships between organizations that want to benefit from direct data collaborations and digital partnerships. They must take responsibility for their own data and fully respect their partner’s data, and the right blend of PETs will provide a platform in which all parties – and their customers – can wholeheartedly put their trust. 

By following the principles of PECC, organizations can address regulatory compliance requirements, reduce the risk of processing sensitive data in the cloud, and enable steadfast digital partnerships with partners. PETs and PECC can act as a catalyst for future data collaborations that drive technological innovation, even between organizations that might ordinarily be in competition with each other. 

The Practical Application of PETs

Several use cases demonstrate the innovative ways PETs transform how sensitive data can be securely and productively employed in collaborative efforts. For example, homomorphic encryption permits the use or analysis of encrypted data without decrypting it in scenarios where organizations want to process data with an external entity. This PET safeguards against any potential malicious actions and ensures neither the cloud service provider nor the external entity can access the raw data.

If several organizations wish to analyze and extract insights from one another’s sensitive datasets while maintaining the confidentiality of their own data, for example, to create audience segments to facilitate better ad targeting, secure multi-party computation (SMPC) permits just this. Differential privacy enables organizations to share insights or derived information with others without exposing any personally identifiable information (PII), enabling a business to create personalized services, for instance, while fully respecting customer privacy.

Even in a scenario where an organization needs to give a third-party access to sensitive data in order to utilize bespoke capabilities for research, machine learning (ML) model training and analysis, synthetic data enables the generation of a version of the data that statistically resembles the real data but does not contain any identifiable or real-world individual data.

PETs, though, are rarely used in isolation. Effective collaborations typically demand a combination of PETs to be employed. For instance, secure multi-party computation and trusted execution environments enable the processing of multiple distributed datasets in-situ, with differential privacy ensuring the insights do not disclose sensitive personal information. This is why PETs can’t be an afterthought and must instead be at the very foundation of data collaboration platforms – if organizations want to seize the opportunities that digital partnerships promise, they must fully embrace the principles of data privacy. 

A Borderless Marketplace for Data Processing and Analytics

There are many applications that PETs could have in industries such as advertising – where through collaboration they can enable secure planning, enrichment, activation, and measurement – or finance, where they can empower the fight against fraud and money laundering. Governments could utilize PETs to facilitate secure online voting and enable smart cities, while healthcare providers could use them to share patient data confidentially and track the spread of diseases. 

Opening up the right datasets in a secure way can also help to drive and accelerate the AI revolution, while mitigating some of the risk associated with these models accessing large volumes of rich and valuable data. By enabling secure pooling of resources and controlled access to distributed sensitive data, it can additionally empower smaller players to train large deep learning models. The potential for data collaborations to open the door for progress in all aspects of business and wider society is enormous; by ensuring these partnerships revolve around the principles of PECC it’s possible to make the world a better place. 

Privacy Must Be the Foundation of Data Collaboration Strategies

PECC is spearheading a transition from simple data sharing to a dynamic, borderless marketplace for data processing and analytics by opening up new possibilities in situations where the risks of data usage had previously overshadowed the benefits.

In scenarios such as encrypted data processing, multi-party processing of distributed data, sharing sensitive data for analysis and research, and training machine learning algorithms, PETs and PECC will enable businesses to reach their individual and shared goals while staying safely within legal frameworks. This is why they must be at the heart of every organization’s data collaboration strategy. 

The trends that are shifting the privacy landscape can’t be ignored or dismissed. Businesses that adapt to and embrace the resultant technological changes will be in the best position to benefit from the opportunities that arise. Privacy is the key that will unlock the full potential of the next generation of data collaboration.