AURORA proposes a risk framework for sustainable smart homes

The Security and Audit Group at the University of Castilla-La Mancha has reported progress in the AURORA research lines alongside the University of Essex’s IADS. The project tackles a problem that is increasingly difficult to address with isolated checklists: how to analyze and manage cybersecurity and sustainability risks together in smart homes, with particular attention to low-density areas such as Castilla-La Mancha.

AURORA proposes building a reusable and parameterized framework. Its first layer uses metadata and ontologies to formalize the meaning of risk analyses and connect them to key risk indicators, or KRIs. This matters because connected homes combine devices, manufacturers, protocols, and very different levels of criticality. A semantic model can help compare scenarios without turning every assessment into a separate document that is difficult to maintain.

The project also considers swarm-intelligence techniques to propagate and manage incidents between nodes with common characteristics. Architecturally, this moves part of the response from an isolated device toward coordination among related entities. That requires clear rules about what information is shared, how it is validated, and what limits prevent a security automation from introducing new privacy or availability risks.

The proposal further includes blockchain infrastructure and smart contracts to provide integrity, traceability, immutability, and consensus around sensitive risk information. These properties do not automatically make a network secure: their value depends on who can write data, what is stored, how permissions are revoked, and what happens when an assessment is wrong. That is why it is relevant that the project treats technology as one component of a management framework rather than as a replacement for threat analysis.

AURORA combines these layers with machine learning applied to security and sustainability datasets. The aim is to discover useful information for prioritizing risks and choosing combinations of controls with lower environmental cost. It also studies quantum-computing algorithms for complex risk-analysis problems. In both cases, these are research lines; they do not mean that a finished product has already been deployed or that commercial results are available.

The regional dimension lies in the technical problem itself. In rural environments, support resources may be farther away, and uneven connectivity can affect device monitoring. A framework combining security, sustainability, automation, and traceability could provide a research basis for designing controls proportional to those conditions. The value of the story is not another connected-device announcement, but an attempt to make the security of a distributed domestic ecosystem auditable and maintainable.