CE25 - Sciences et génie du logiciel - Réseaux de communication multi-usages, infrastructures de hautes performances

Hardware & software architectures for real time Radio Frequency fingerprint identification for TEMPEST attacks – RedInBlack

Submission summary

TEMPEST attacks targets device that unintentionally emits sensible data through an electromagnetic channel. This kind of compromising are due to coupling, hardware impairments or physical proximity between components. Sensitive information emitted by these devices may be recovered passively by any radio component and more particularly by software defined radio, now capable to sample very large bandwidths.
The objectives of RedInBlack are many-folds
- Assess new radio fingerprint based methods to identify devices through learning methods fed by large bandwidths features
- Propose coherent and non coherent decoding methods to recover the sensitive data emitted by the device
- Develop effective methods able to cope with large bandwidths to identify TEMPEST channel and recover sensitive data in real time with the use of a new hardware/software methodology based on Julia langage.

Project coordination

Robin GERZAGUET (Université Rennes 1)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

IRISA Université Rennes 1

Help of the ANR 284,251 euros
Beginning and duration of the scientific project: March 2023 - 42 Months

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