Novel approaches to finding vulnerabilities in Quantum Secure Communications

Project funded by Fundação para a Ciência e a Tecnologia, I.P. (FCT), grant 2024.06303.BDANA. Runs 2025-04-01 to 2029-03-31. Source: OpenAIRE Graph, from the funder's project data (collected by OpenAIRE on 2026-06-26); national funding data, not CORDIS. Abstract given by the source: My work will focus on performing electronic side-channel analysis to Quantum Key Distribution networks and formulating countermeasures to mitigate the information leakage caused by the found vulnerabilities in the system. Focusing primarily on electromagnetic and power side-channels, I will consider different methods for data treatment, implementing simple side-channel analysis techniques via neural networks, together with correlation side-channel analysis, which has yet to be applied to QKD. With the latter, I believe to improve the results already obtained for electromagnetic radiation analysis. The electromagnetic side-channel analysis will be performed in the near-field and far-field region, and the power side-channel analysis in the AC and DC regime, with the primary objective of simulating eavesdropping at the most realistic conditions. Finally, optical side-channels arising as a consequence of unexpected electronic behaviour in the QKD transmitter will also be explored.

Original source.

Source: OpenAIRE Graph: projects of national funders, OpenAIRE, from the project data of Fundação para a Ciência e a Tecnologia, I.P. (FCT). Retrieved 2026-10-22. Licence: Creative Commons Attribution 4.0 (OpenAIRE Graph). Selected metadata, adapted presentation; the publisher's record is authoritative. No endorsement by the source is implied. Licence: Creative Commons Attribution 4.0 (CC BY 4.0).

AI-assisted summary: The project, funded by FCT, runs from April 2025 to March 2029 and focuses on electronic side-channel analysis of Quantum Key Distribution networks to identify vulnerabilities and develop countermeasures against information leakage. Suggested technology pillar: communication. Generated by AI from the public source text; it may contain errors and the original source is authoritative.