The arrival of eIDAS 2.0 demands a fundamental shift in mindset for organizations when it comes to secure data exchange. We should not just be thinking in terms of technical infrastructure, but focusing instead on the intrinsic trustworthiness of the data itself.
In this new era of digital collaboration across Europe, the reliability of information becomes just as critical as the security of the channels through which it flows. For semi-governments and policy makers – important enablers in the secure data exchange evolution – the key to navigating this transition lies in choosing the right data exchange model that fits your role within the ecosystem.
A history of maintaining trust in data exchange
Secure data exchange has long centered on protecting information from tampering, ensuring authenticity, and reliably delivering it to the right recipient. Historically, this was achieved through physical methods: trusted couriers, handwritten signatures, official seals, and special paper all played a role in maintaining trust. Tamper-evident seals and detailed chain of custody records added further layers of protection, making it clear if a document had been altered or accessed during transit.
While these techniques were effective for their time, they were also labor-intensive, costly, and not suited to the scale and speed demanded by today’s digital world. As data exchange evolved, the focus shifted from physical assurances to digital trust mechanisms.
Moving from physical to digital methods
This evolution introduced cryptographic models as the foundation for modern secure communication. Digital signatures replaced handwritten ones, ensuring both authenticity and non-repudiation. Encryption algorithms now protect data in transit, making interception useless without the correct decryption keys. Public Key Infrastructure (PKI) became a cornerstone, enabling secure identity verification and trust relationships across systems and borders.
These cryptographic techniques allow for scalable, automated, and tamper-proof exchanges, laying the groundwork for frameworks like eIDAS 2.0 and the trust services that power today’s digital economy.
Trust is key
Despite the shift from physical to digital methods, the fundamental challenge remains unchanged: trust. Organizations still need to be certain that the data they receive is authentic, untampered, and comes from a legitimate source. In digital environments, where interactions are faster and often anonymous, verifying both the integrity of the data and the identity of the sender becomes even more critical. Without built-in trust mechanisms, even the most secure technical systems can fall short – highlighting the ongoing need to embed trust not just in the transmission, but in the data itself and the ecosystem that supports its exchange.
Secure data exchange today: five models
For semi-government organizations and policymakers, secure data exchange is essential to fulfilling their public responsibilities in a trustworthy and efficient manner. These entities often operate at the intersection of public and private sectors, handling sensitive information such as personal data, legal records, or regulatory filings. Any compromise in the integrity, confidentiality, or authenticity of this data can have serious consequences.
Moreover, as governments push for more integrated digital services and cross-border collaboration, especially under the eIDAS 2.0 framework, the ability to securely and reliably exchange data becomes a foundational requirement. It's not just about compliance or security: it's about enabling seamless cooperation, informed policymaking, and better service delivery in a rapidly digitizing society.
Organizations therefore need more than just secure connections: they need a clear strategy for how data is exchanged within and across ecosystems. This is where the choice of data exchange model becomes critical.
Secure data exchange models
The landscape of secure data exchange can be broken down into five technical models, each reflecting a different stage of digital maturity and level of trust assurance.
1. Sneakernet
The first is the Sneakernet model, where data is physically transported using portable storage devices like USB sticks or external hard drives. While this approach avoids exposure to network-based attacks, it carries many of the same risks as historical courier systems, such as loss, theft, or tampering during transit, and offers little scalability or real-time access.
2. Own Database
Next is the Own Database model, in which organizations manage sensitive data internally within secured systems. Access is controlled using encryption, authentication, and monitoring tools. While this setup simplifies data governance and can be tightly controlled, it also introduces a single point of failure: if the system is breached or misconfigured, the entire dataset may be at risk.
3. Authenticated Connections
The third model involves Authenticated Connections, using protocols like HTTPS and TLS to create secure, encrypted communication channels between systems. This approach protects data in transit from interception or tampering and is foundational to any secure online interaction. However, it focuses on securing the channel, not necessarily the data itself.
4. Federated Authentication
The fourth model is Federated Authentication, which streamlines identity management across multiple systems. Here, users authenticate through a central identity provider, allowing them access to various services without needing separate credentials for each. This model enhances user experience and reduces security risks related to password reuse, while still relying on trusted relationships between identity providers and service platforms.
5. Authenticated Data
The fifth and most advanced model is Authenticated Data. Instead of focusing solely on the channel or the systems involved, this approach embeds trust directly into the data itself. There are several forms of authenticated data:
- In the "Phone Home" method, data verifies its authenticity by reaching back to a trusted source or registry.
- In the Inherent/Signed method, the data carries cryptographic signatures, allowing recipients to verify authenticity independently of the source.
- The "Meet in the Middle" approach involves external platforms or shared infrastructures to verify data, such as:
- Blockchain, which offers decentralized, tamper-evident records.
- Data Exchange Platforms, which act as trusted intermediaries to facilitate and log secure sharing between parties.
Each of these models offers different levels of control, trust, and scalability. As digital ecosystems grow in complexity, organizations are increasingly moving toward models where data can prove its own authenticity, enabling secure exchange even in loosely coupled, cross-domain environments.
Secure data exchange in the real world
Secure data exchange plays a vital role in various real-world systems, enabling organizations to operate efficiently, safely, and at scale. In enterprise environments, systems like SAP use a model based on maintaining an internal database paired with authenticated connections. This allows businesses to centralize essential processes such as finance, logistics, and human resources, while ensuring that users access data over encrypted channels. It simplifies management and strengthens security through access controls, but it also comes with significant setup costs and the risk of downtime if the central infrastructure fails.
In the public sector, systems like DigiD in the Netherlands demonstrate the power of federated authentication. By allowing citizens to use a single, trusted digital identity to access a wide range of government services, DigiD improves convenience and reduces administrative overhead. However, its effectiveness hinges on the security and reliability of the central identity provider; if compromised, the entire ecosystem could be at risk.
The financial sector showcases even more complex integrations, as seen in open banking initiatives. These rely on a mix of federated authentication and authenticated connections, allowing consumers to share financial data securely with third-party services via APIs. This model fosters innovation and gives users greater control over their data, though it also introduces new challenges around API security and interoperability.
In the world of payments, the EMV standard, which is used in chip-enabled debit and credit cards, illustrates the concept of authenticated data. Each transaction generates a unique cryptographic signature, allowing it to be independently verified and reducing the risk of fraud or tampering. While this system is widely adopted and highly effective, it requires substantial investment in infrastructure and may not be compatible with older payment systems in some regions.
Taking action: what does this mean for you as a semi-government organization?
As a semi-governmental organization, the shift toward secure and trustworthy digital collaboration, driven by eIDAS 2.0, is not just a technical upgrade; it's a strategic opportunity. Your role in the data ecosystem is evolving, and now is the time to take a proactive stance.
What’s your role?
First, clarify your position in the trust chain. Are you primarily an issuer of data, a holder, a verifier, or a combination of these roles? Each position comes with its own responsibilities and technical requirements. Issuers must ensure data is signed and verifiable. Holders need systems to manage and present this data securely. Verifiers must be able to independently check the authenticity and origin of what they receive. Understanding your role is the first step in building or joining a trustworthy digital ecosystem.
Review your IT architecture
Next, review your current IT architecture. Can your systems handle signed and verifiable data? Are you equipped to store, transmit, and validate data in line with modern cryptographic standards? If not, it’s crucial to start modernizing your infrastructure: not just for compliance, but to stay relevant and interoperable in a more connected public sector.
Review your compliance needs
You should also invest in the adoption of common standards. Embracing frameworks like eIDAS 2.0, Verifiable Credentials, and open data exchange platforms ensures you’re not working in isolation. These standards create shared trust, reduce fragmentation, and support smoother collaboration across borders, domains, and levels of government.
Take control of your role
Finally, take control of your role in the ecosystem. Don’t limit your organization to being a passive executor of policies or services. Instead, become a builder of trust in your region or sector. By actively shaping how data is exchanged and verified, you contribute not just to security and compliance – but to better, more reliable public services for everyone.
Conclusion
Simply being eIDAS 2.0 compliant is no longer enough. The real question for organizations, especially semi-governments, is how to ensure that the data they exchange is trusted – both within their own systems and with external partners. As the custodians of sensitive information and public services, semi-governments are not just the executors of policy but also key enablers in creating and maintaining a reliable digital ecosystem.
By adopting the right models for secure data exchange, whether it's through trusted databases, authenticated connections, or verifiable data, semi-governments can ensure that their systems are not only secure but also capable of fostering trust across the broader digital landscape. These models offer a blueprint for how to safeguard the integrity and authenticity of data, providing the building blocks necessary for seamless collaboration. As the digital landscape continues to evolve, semi-governments must embrace their role as both leaders and guardians of trust, ensuring that they remain at the forefront of secure and reliable digital interactions.
Want to know more about how Ubiqu can help you in this process? Get in touch with us.
