Accelerating Transition to Post-Quantum Cryptography

Project funded by Research Council of Finland, grant 375829. Participating organisations named by the source: Aalto University. Funded amount: EUR 515,360, as stated by the source. Runs 2026-09-01 to 2030-08-31. Keywords: Computer and information sciences. Source: OpenAIRE Graph, from the funder's project data (collected by OpenAIRE on 2026-07-06); national funding data, not CORDIS. Abstract given by the source: The rapid advancement of quantum computing threatens the security of todays widely deployed cryptography. There is an urgent societal need to transition to post-quantum cryptography, protecting the worlds digital infrastructure against quantum-enabled adversaries. Although basic post-quantum primitives for securing end-to-end communication have now been standardised, many complex digital systems, such as digital identity and privacy-preserving machine learning, still lack post-quantum cybersecurity solutions that are as practical as their quantum-insecure counterparts. The project ATPQC, which will be hosted by the Department of Computer Science at Aalto University, aims to fill this gap by designing advanced cryptographic schemes for complex applications that are both practical and post-quantum secure, while also developing the underlying theoretical tools for analysing the security of these schemes.

Original source.

Source: OpenAIRE Graph: projects of national funders, OpenAIRE, from the project data of Research Council of Finland. 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 ATPQC, funded by the Research Council of Finland, aims to develop practical post-quantum cryptographic solutions for complex digital systems, hosted by Aalto University from 2026 to 2030. Suggested technology pillar: communication. Generated by AI from the public source text; it may contain errors and the original source is authoritative.