After four stages of research and development, the SecBluRed project concludes successfully. amplía))) has validated prototypes in identity, traceability and artificial intelligence that strengthen the cybersecurity and resilience of IIoT environments, while also collaborating with the rest of the consortium partners to achieve all the objectives of the SecBluRed project.

A project that comes to an end

The SecBluRed project (Holistic approach to cybersecurity in Industrial IoT) comes to its close after four years of intense collaborative work. At amplía))) we would like to thank CDTI and the European Union – NextGenerationEU, as well as all the consortium partners, for their support and trust throughout this shared journey towards cybersecurity innovation.

Our prototypes: identity, traceability and proactive detection with UEBA

Throughout the project, amplía))) has contributed to the development and validation of prototypes in two key areas:

• Identity and traceability. We have designed and tested mechanisms for decentralized identity and Distributed Ledger Technologies (DLTs) to ensure the trustworthiness of devices and the immutability of their messages. Prototypes based on IoTA Identity, Hyperledger Fabric and Hedera Consensus Service, integrated into our OpenGate platform, have demonstrated the feasibility of securely identifying, recording, signing and verifying device transactions in a reliable and auditable way.

• Artificial intelligence applied to cybersecurity. We have developed UEBA (User and Entity Behavior Analytics) models based on AI for the early detection of anomalies in IIoT traffic. These models were validated using anonymized real-world data, synthetic anomalies and benchmark datasets, confirming significant improvements in accuracy and detection capability compared to traditional approaches. We will continue studying how best to integrate these advances into our portfolio of solutions.

General conclusions

The project results confirm that:

• Decentralized identity and traceability through DLTs provide an additional layer of trust and transparency in complex IIoT ecosystems. It is true, however, that they imply additional costs in computation and resource management in order to fully leverage the capabilities of decentralized networks.
• AI applied to monitoring enables more proactive and reliable threat detection, reducing false positives and improving response capacity. By carefully selecting and applying the right AI models, each use case can be addressed in the most effective way for its problem domain—though this also entails higher computational demands when models are deployed for inference.
• There are positive side effects: anomaly detection can identify not only cybersecurity threats, but also malfunctioning devices or process failures caused by incorrect firmware/software versions or configuration errors. This means such mechanisms can also be exploited for optimizing IIoT solutions where they are applied.
• The validation of the integration of these solutions into OpenGate as an IoT platform opens the door to practical application in critical industrial sectors such as energy generation (traditional and renewable) or transport—both essential infrastructures that must continually strengthen their security—as well as in other processes, solutions and industries such as manufacturing.

Looking ahead

With the conclusion of SecBluRed, at amplía))) we close a stage of research and open another of technological evolution. The lessons learned and the validated prototypes will be incorporated into our product roadmap, reinforcing the security and trust of the IIoT solutions we offer our clients, and helping us adapt to the ongoing changes the sector faces every day in the management of its cybersecurity.